References

Abernathy, P. M. (2020). News deserts and ghost newspapers: Will local news survive. University of North Carolina Press.
Acemoglu, D. (2024). Harms of AI. In J. B. Bullock, Y.-C. Chen, J. Himmelreich, V. M. Hudson, A. Korinek, M. M. Young, & B. Zhang (Eds.), The Oxford handbook of AI governance (pp. 660–706). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780197579329.013.65
Acemoglu, D., & Johnson, S. (2023). Power and progress: Our thousand-year struggle over technology and prosperity. PublicAffairs.
Acemoglu, D., & Restrepo, P. (2019). Artificial intelligence, automation and work. In A. Agrawal, J. Gans, & A. Goldfarb (Eds.), The economics of artificial intelligence: An agenda (pp. 197–236). The University of Chicago Press.
Acemoglu, D., & Restrepo, P. (2022a). Demographics and automation. The Review of Economic Studies, 89(1), 1–44. https://doi.org/10.1093/restud/rdab031
Acemoglu, D., & Restrepo, P. (2022b). Tasks, automation, and the rise in U.S. Wage inequality. Econometrica, 90(5), 1973–2016. https://doi.org/10.3982/ECTA19815
Acerbi, A. (2020). Cultural evolution in the digital age. Oxford University Press. https://doi.org/10.1093/oso/9780198835943.001.0001
Achen, C. H., & Bartels, L. M. (2016). Democracy for realists: Why elections do not produce responsive government. Princeton University Press. https://doi.org/10.2307/j.ctvc7770q
Agarwal, S. D., & Barthel, M. L. (2015). The friendly barbarians: Professional norms and work routines of online journalists in the united states. Journalism, 16(3), 376–391. https://doi.org/10.1177/1464884913511565
Agrawal, A., Gans, J., & Goldfarb, A. (2022). Prediction machines: The simple economics of artificial intelligence (Updated and Expanded). Harvard Business Review Press. (Original work published 2018)
Ahmed, N., Wahed, M., & Thompson, N. C. (2023). The growing influence of industry in AI research. Science, 379(6635), 884–886. https://doi.org/10.1126/science.ade2420
Alam, M. R., Reaz, M. B. I., & Ali, M. A. M. (2012). A review of smart homes – past, present, and future. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 42(6), 1190–1203. https://doi.org/10.1109/TSMCC.2012.2189204
Allen, J., Howland, B., Mobius, M., Rothschild, D., & Watts, D. J. (2020). Evaluating the fake news problem at the scale of the information ecosystem. Science Advances, 6(14), eaay3539. https://doi.org/10.1126/sciadv.aay3539
Almqvist, M. F. (2016). Piracy and the politics of social media. Social Sciences, 5(3), 41. https://doi.org/10.3390/socsci5030041
Alpaydin, E. (2021). Machine learning (Revised and updated). The MIT Press. (Original work published 2016)
An, J., Kwak, H., Posegga, O., & Jungherr, A. (2019). Political discussions in homogeneous and cross-cutting communication spaces. In J. Pfeffer, C. Budak, Y.-R. Lin, & F. Morstatter (Eds.), ICWSM 2019: Proceedings of the thirteenth international AAAI conference on web and social media (pp. 68–79). Association for the Advancement of Artificial Intelligence (AAAI).
Anderson, B. (2016). Imagined communities: Reflections on the origin and spread of nationalism (Revised). Verso.
Angrist, J. D., & Pischke, J.-S. (2010). The credibility revolution in empirical economics: How better research design is taking the con out of econometrics. Journal of Economic Perspectives, 24(2), 3–30. https://doi.org/10.1257/jep.24.2.3
Anstead, N., & O’Loughlin, B. (2015). Social media analysis and public opinion: The 2010 UK General Election. Journal of Computer-Mediated Communication, 20(2), 204–220. https://doi.org/10.1111/jcc4.12102
Asimov, I. (1955). Franchise. If: Worlds of Science Fiction, August, 2–15. https://ia801300.us.archive.org/25/items/1955-08_IF/1955-08_IF.pdf
Auletta, K. (2009). Googled: The end of the world as we know it. The Penguin Press.
Auletta, K. (2018). Frenemies: The epic disruption of the ad business (and everything else). Penguin Press.
Auxier, B., & Anderson, M. (2021). Social media use in 2021. Pew Research Center. https://www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021/
Aviram, H., Bragg, A., & Lewis, C. (2017). Felon disenfranchisement. Annual Review of Law and Social Science, 13, 295–311. https://doi.org/10.1146/annurev-lawsocsci-110316-113558
Badue, C., Guidolini, R., Carneiro, R. V., Azevedo, P., Cardoso, V. B., Forechi, A., Jesus, L., Berriel, R., Paixão, T. M., Mutz, F., Paula Veronese, L. de, Oliveira-Santos, T., & Souza, A. F. D. (2021). Self-driving cars: A survey. Expert Systems with Applications, 165(1), 113816. https://doi.org/10.1016/j.eswa.2020.113816
Bai, H., Voelkel, J. G., Eichstaedt, J. C., & Willer, R. (2023). Artificial intelligence can persuade humans on political issues. OSF Preprints. https://doi.org/10.31219/osf.io/stakv
Bail, C. A., Argyle, L. P., Brown, T. W., Bumpus, J. P., Chen, H., Hunzaker, M. B. F., Lee, J., Mann, M., Merhout, F., & Volfovsky, A. (2018). Exposure to opposing views on social media can increase political polarization. PNAS: Proceedings of the National Academy of Sciences, 115(37), 9216–9221. https://doi.org/10.1073/pnas.1804840115
Ball, M. (2022). The Metaverse: And how it will revolutionize everything. Liveright Publishing Corporation.
Barberá, P. (2015). Birds of the same feather tweet together: Bayesian ideal point estimation using Twitter data. Political Analysis, 23(1), 76–91. https://doi.org/10.1093/pan/mpu011
Barberá, P., Boydstun, A. E., Linn, S., McMahon, R., & Nagler, J. (2021). Automated text classification of news articles: A practical guide. Political Analysis, 29(1), 19–42. https://doi.org/10.1017/pan.2020.8
Barbrook, R., & Cameron, A. (1995). The californian ideology. Mute, 1(3). https://www.metamute.org/editorial/articles/californian-ideology
Barlow, J. P. (1996). A declaration of the independence of cyberspace. EFF: Electronic Frontier Foundation. https://www.eff.org/cyberspace-independence
Barocas, S., Hardt, M., & Narayanan, A. (2023). Fairness and machine learning: Limitations and opportunities. The MIT Press.
Barocas, S., & Selbst, A. D. (2016). Big data’s disparate impact. California Law Review, 104, 671–732. https://doi.org/10.15779/Z38BG31
Baron, J. (2023). Thinking and deciding (5th ed.). Cambridge University Press. https://doi.org/10.1017/9781009263672 (Original work published 1988)
Barron, A. T. J., Huang, J., Spang, R. L., & DeDeo, S. (2018). Individuals, institutions, and innovation in the debates of the French Revolution. PNAS: Proceedings of the National Academy of Sciences, 115(18), 4607–4612. https://doi.org/10.1073/pnas.1717729115
Baumgartner, F. R., Boef, S. D., & Boydstun, A. E. (2008). The decline of the death penalty and the discovery of innocence. Cambridge University Press. https://doi.org/10.1017/CBO9780511790638
Beauchamp, N. (2017). Predicting and interpolating state-level polling using Twitter textual data. American Journal of Political Science, 61(2), 490–503. https://doi.org/10.1111/ajps.12274
Bechar, A., & Vigneault, C. (2016). Agricultural robots for field operations: Concepts and components. Biosystems Engineering, 149, 94–111. https://doi.org/10.1016/j.biosystemseng.2016.06.014
Beieler, J., Brandt, P. T., Halterman, A., Schrodt, P. A., & Simpson, E. M. (2016). Generating political event data in near real time. In R. M. Alvarez (Ed.), Computational social science: Discovery and prediction (pp. 98–120). Cambridge University Press. https://doi.org/10.1017/CBO9781316257340.005
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In FAccT ’21: Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610–623). Association for Computing Machinery. https://doi.org/10.1145/3442188.3445922
Bengfort, B., Bilbro, R., & Ojeda, T. (2018). Applied text analysis with python: Enabling language aware data products with machine learning. O’Reilly Media.
Benkler, Y. (2006). The wealth of networks: How social production transforms markets and freedom. Yale University Press.
Benkler, Y. (2011). The penguin and the leviathan: How cooperation triumphs over self-interest. Crown Publishing Group.
Bennett, W. L. (1990). Towards a theory of press-state relations in the US. Journal of Communication, 40(2), 103–125. https://doi.org/10.1111/j.1460-2466.1990.tb02265.x
Bennett, W. L. (2005). Beyond pseudoevents: Election news as reality TV. American Behavioral Scientist, 49(3), 364–378. https://doi.org/10.1177/0002764205280919
Bennett, W. L. (2016). News: The politics of illusion (10th ed.). The University of Chicago Press. (Original work published 1983)
Bennett, W. L., & Livingston, S. (2018). The disinformation order: Disruptive communication and the decline of democratic institutions. European Journal of Communication, 33(2), 122–139. https://doi.org/10.1177/0267323118760317
Bennett, W. L., & Livingston, S. (Eds.). (2021). The disinformation age: Politics, technology, and disruptive communication in the United States. Cambridge University Press. https://doi.org/10.1017/9781108914628
Bennett, W. L., & Manheim, J. B. (2006). The one-step flow of communication. The ANNALS of the American Academy of Political and Social Science, 608(1), 213–232. https://doi.org/10.1177/0002716206292266
Bennett, W. L., & Segerberg, A. (2013). The logic of connective action: Digital media and the personalization of contentious politics. Cambridge University Press. https://doi.org/10.1017/CBO9781139198752
Benoit, K. (2020). Text as data: An overview. In L. Cuirini & R. Franzese (Eds.), The SAGE handbook of research methods in political science and international relations (pp. 461–497). SAGE Publications. https://doi.org/10.4135/9781526486387.n29
Benoit, K., Watanabe, K., Wang, H., Nulty, P., Obeng, A., Müller, S., & Matsuo, A. (2018). Quanteda: An R package for the quantitative analysis of textual data. Journal of Open Source Software, 3(30), 1–4. https://doi.org/10.21105/joss.00774
Bergen, M. (2022). Like, comment, subscribe: Inside YouTube’s chaotic rise to world domination. Viking.
Bessen, J. (2022). New goliaths: How corporations use software to dominate industries, kill innovation, and undermine regulation. Yale University Press.
Bi, Z., & Wang, X. (2020). Computer aided design and manufacturing. John Wiley & Sons.
Bimber, B. (2003). Information and American democracy: Technology in the evolution of political power. Cambridge University Press. https://doi.org/10.1017/CBO9780511615573
Bisbee, J., Clinton, J., Dorff, C., Kenkel, B., & Larson, J. (2023). Artificially precise extremism: How internet-trained LLMs exaggerate our differences. SocArxiv. https://doi.org/10.31235/osf.io/5ecfa
Black, F. (1971a). Toward a fully automated stock exchange, part i. Financial Analysts Journal, 27(4), 28–35. https://doi.org/10.2469/faj.v27.n4.28
Black, F. (1971b). Toward a fully automated stock exchange, part II. Financial Analysts Journal, 27(6), 24–28. https://doi.org/10.2469/faj.v27.n6.24
Blei, D. M., & Lafferty, J. D. (2007). A correlated topic model of Science. The Annals of Applied Statistics, 1(1), 17–35. https://doi.org/10.1214/07-AOAS114
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.
Boast, R. (2017). The machine in the ghost: Digitality and its consequences. Reaktion Books.
Boczkowski, P. J., & Papacharissi, Z. A. (2018). Trump and the media (P. J. Boczkowski & Z. A. Papacharissi, Eds.). The MIT Press.
Bolukbasi, T., Chang, K.-W., Zou, J., Saligrama, V., & Kalai, A. (2016). Man is to computer programmer as woman is to homemaker? Debiasing word embeddings. In D. D. Lee, U. von Luxburg, R. Garnett, M. Sugiyama, & I. Guyon (Eds.), NIPS’16: Proceedings of the 30th international conference on neural information processing systems (pp. 4356–4364). Curran Associates Inc. https://doi.org/10.5555/3157382.3157584
Bond, B., & Exley, Z. (2016). Rules for revolutionaries: How big organizing can change everything. Chelsea Green Publishing.
Bor, A., & Petersen, M. B. (2022). The psychology of online political hostility: A comprehensive, cross-national test of the mismatch hypothesis. American Political Science Review, 116(1), 1–18. https://doi.org/10.1017/S0003055421000885
Borges, J. L. (1975). On exactitude in science. In N. T. di Giovanni (Trans.), A universal history of infamy (p. 131). Penguin Books. (Original work published 1946)
Borgesius, F. J. Z., Trilling, D., Möller, J., Bodó, B., Vreese, C. H. de, & Helberger, N. (2016). Should we worry about filter bubbles? Internet Policy Review, 5(1), 1–16. https://doi.org/10.14763/2016.1.401
Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
Bourdieu, P. (1990). Social space and symbolic power. In In other words: Essays towards a reflexive sociology (pp. 123–139). Stanford University Press.
Bowker, G. C., & Star, S. L. (1999). Sorting things out: Classification and its consequences. The MIT Press.
Bradford, A. (2020). The brussels effect: How the european union rules the world. Oxford University Press. https://doi.org/10.1093/oso/9780190088583.001.0001
Brandt, M., Tucker, C. J., Kariryaa, A., Rasmussen, K., Abel, C., Small, J., Chave, J., Rasmussen, L. V., Hiernaux, P., Diouf, A. A., Kergoat, L., Mertz, O., Igel, C., Gieseke, F., Schöning, J., Li, S., Melocik, K., Meyer, J., Sino, S., … Fensholt, R. (2020). An unexpectedly large count of trees in the West African Sahara and Sahel. Nature, 587(7832), 78–82. https://doi.org/10.1038/s41586-020-2824-5
Brayne, S. (2021). Predict and surveil: Data, discretion, and the future of policing. Oxford University Press. https://doi.org/10.1093/oso/9780190684099.001.0001
Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32. https://doi.org/10.1023/A:1010933404324
Brennen, J. S., & Kreiss, D. (2016). Digitalization. In The international encyclopedia of communication theory and philosophy (pp. 1–11). John Wiley & Sons. https://doi.org/10.1002/9781118766804.wbiect111
Brodersen, K. H., Gallusser, F., Koehler, J., Remy, N., & Scott, S. L. (2015). Inferring causal impact using Bayesian structural time-series models. The Annals of Applied Statistics, 9(1), 247–274. https://doi.org/10.1214/14-AOAS788
Brown, E., & Farrell, M. (2021). The cult of we: WeWork, adam neumann, and the great startup delusion. Crown Publishing Group.
Brown, M. A., & Zhou, S. (2019). Smart-grid policies: An international review. In P. D. Lund, J. Byrne, R. Haas, & D. Flynn (Eds.), Advances in energy systems: The large‐scale renewable energy integration challenge (pp. 127–147). John Wiley & Sons. https://doi.org/10.1002/9781119508311.ch8
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language models are few-shot learners. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), Advances in neural information processing systems (Vol. 33, pp. 1877–1901). Curran Associates, Inc. https://proceedings.neurips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf
Brussee, V. (2023). Social credit: The warring states of China’s emerging data empire. Palgrave Macmillan. https://doi.org/10.1007/978-981-99-2189-8
Bryant, J., & Oliver, M. B. (Eds.). (2009). Media effects: Advances in theory and research (3rd ed.). Routledge.
Brynjolfsson, E., Jin, W., & Wang, X. (2023). Information technology, firm size, and industrial concentration. NBER Working Paper, 31065. https://doi.org/10.3386/w31065
Brynjolfsson, E., & McAfee, A. (2016). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.
Buchanan, B., & Imbrie, A. (2022). The new fire: War, peace, and democracy in the age of AI. The MIT Press.
Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. In S. A. Friedler & C. Wilson (Eds.), Proceedings of the 1st conference on fairness, accountability and transparency (Vol. 81, pp. 77–91). Proceedings of Machine Learning Research (PMLR). https://proceedings.mlr.press/v81/buolamwini18a.html
Burton, J. W., Cruz, N., & Hahn, U. (2021). Reconsidering evidence of moral contagion in online social networks. Nature Human Behavior, 5, 1629–1635. https://doi.org/10.1038/s41562-021-01133-5
Buyalskaya, A., Gallo, M., & Camerer, C. F. (2021). The golden age of social science. PNAS: Proceedings of the National Academy of Sciences, 118(5), 1–11. https://doi.org/10.1073/pnas.2002923118
Calhoun, C., Gaonkar, D. P., & Taylor, C. (2022). Degenerations of democracy. Harvard University Press.
Caliskan, A., Bryson, J. J., & Narayanan, A. (2017). Semantics derived automatically from language corpora contain human-like biases. Science, 356(6334), 183–186. https://doi.org/10.1126/science.aal4230
Camargo, C. Q., & Simon, F. M. (2022). Mis- and disinformation studies are too big to fail: Six suggestions for the field’s future. Harvard Kennedy School Misinformation Review, 3(5), 1–9. https://doi.org/10.37016/mr-2020-106
Cardella, L., Hao, J., Kalcheva, I., & Ma, Y.-Y. (2014). Computerization of the equity, foreign exchange, derivatives, and fixed-income markets. The Financial Review, 49(2), 231–243. https://doi.org/10.1111/fire.12033
Carlson, M., Robinson, S., & Lewis, S. C. (2021). News after Trump: Journalism’s crisis of relevance in a changed media culture. Oxford University Press. https://doi.org/10.1093/oso/9780197550342.001.0001
Carreyou, J. (2018). Bad blood: Secrets and lies in a silicon valley. Alfred A. Knopf.
Casero-Ripollés, A., Feenstra, R. A., & Tormey, S. (2016). Old and new media logics in an electoral campaign: The case of podemos and the two-way street mediatization of politics. The International Journal of Press/Politics, 21(3), 378–397. https://doi.org/10.1177/1940161216645340
Castells, M. (2001). The internet galaxy: Reflections on the internet, business and society. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199255771.001.0001
Castells, M. (2013). Communication power (2nd ed.). Oxford University Press. (Original work published 2009)
Chabert, J.-L. (Ed.). (1999). A history of algorithms: From the pebble to the microchip (C. Weeks, Trans.). Springer. https://doi.org/10.1007/978-3-642-18192-4 (Original work published 1994)
Chafkin, M. (2021). The contrarian: Peter Thiel and Silicon Valley’s pursuit of power. Penguin Books.
Chen, L., Zhang, C., & Wilson, C. (2013). Tweeting under pressure: Analyzing trending topics and evolving word choice on Sina Weibo. In M. Muthukrishnan, A. El Abbadi, & B. Krishnamurthy (Eds.), COSN ’13: Proceedings of the first ACM conference on online social networks (pp. 89–100). ACM. https://doi.org/10.1145/2512938.2512940
Chia, A., Keogh, B., Leorke, D., & Nicoll, B. (2020). Platformisation in game development. Internet Policy Review, 9(4), 1–28. https://doi.org/10.14763/2020.4.1515
Cho, W. K. T., & Cain, B. E. (2020). Human-centered redistricting automation in the age of AI. Science, 369(6508), 1179–1181. https://doi.org/10.1126/science.abd1879
Chouldechova, A. (2017). Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. Big Data, 5(2), 153–163. https://doi.org/10.1089/big.2016.0047
Chow, S., Liver, S., & Nelson, A. (2018). Streamlining bioactive molecular discovery through integration and automation. Nature Reviews Chemistry, 2, 174–183. https://doi.org/10.1038/s41570-018-0025-7
Christensen, G., Freese, J., & Miguel, E. (2019). Transparent and reproducible social science research: How to do open science. University of California Press.
Christian, B. (2020). The alignment problem: Machine learning and human values. W. W. Norton & Company.
Christians, C. G., Glasser, T. L., McQuail, D., Nordenstreng, K., & White, R. A. (2009). Normative theories of the media: Journalism in democratic societies. University of Illinois Press.
Christin, A. (2020). Metrics at work: Journalism and the contested meaning of algorithms. Princeton University Press.
Cirone, A., & Spirling, A. (2021). Turning history into data: Data collection, measurement, and inference in HPE. Journal of Historical Political Economy, 1(1), 127–154. https://doi.org/10.1561/115.00000005
Citron, D. K., & Pasquale, F. (2014). The scored society: Due process fo automated predictions. Washington Law Review, 89(1), 1–33.
Clark, D. (2016). Alibaba: The house that Jack Ma built. Harper Collins.
Cogburn, D. L., & Espinoza-Vasquez, F. K. (2011). From networked nominee to networked nation: Examining the impact of web 2.0 and social media on political participation and civic engagement in the 2008 obama campaign. Journal of Political Marketing, 10(1-2), 189–213. https://doi.org/10.1080/15377857.2011.540224
Cohen, I. G., Gostin, L. O., & Weitzner, D. J. (2020). Digital smartphone tracking for COVID-19: Public health and civil liberties in tension. JAMA, 323(23), 2371–2372. https://doi.org/10.1001/jama.2020.8570
Cohen, J. E. (2012). Configuring the networked self: Law, code, and the play of everyday practice. Yale University Press.
Cohen, J. E. (2013). What privacy is for. Harvard Law Review, 126(7), 1904–1933.
Cohen, J. E. (2019). Between truth and power: The legal constructions of informational capitalism. Oxford University Press. https://doi.org/10.1093/oso/9780190246693.001.0001
Converse, P. (1964). The nature of belief systems in mass publics. In D. E. Apter (Ed.), Ideology and discontent (pp. 206–261). Free Press.
Coppock, A., Hill, S. J., & Vavreck, L. (2020). The small effects of political advertising are small regardless of context, message, sender, or receiver: Evidence from 59 real-time randomized experiments. Science Advances, 6(36), 1–6. https://doi.org/10.1126/sciadv.abc4046
Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2022). Introduction to algorithms (4th ed.). The MIT Press. (Original work published 1990)
Cotter, K. (2019). Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram. New Media & Society, 21(4), 895–913. https://doi.org/10.1177/1461444818815684
Crain, M. (2021). Profit over privacy: How surveillance advertising conquered the internet. University of Minnesota Press.
Creemers, R. (2017). Cyber China: Upgrading propaganda, public opinion work and social management for the twenty-first century. Journal of Contemporary China, 26(103), 85–100. https://doi.org/10.1080/10670564.2016.1206281
Creemers, R. (2018). China’s social credit system: An evolving practice of control. Social Science Research Network. https://doi.org/10.2139/ssrn.3175792
Crosby, A. W. (1996). The measure of reality: Quantification in western europe, 1250–1600. Cambridge University Press. https://doi.org/10.1017/CBO9781107050518
Dahl, R. A. (1998). On democracy. Yale University Press.
Daston, L. (2022). Rules: A short history of what we live by. Princeton University Press.
DellaPosta, D., Shi, Y., & Macy, M. (2015). Why do Liberals drink Lattes? American Journal of Sociology, 120(5), 1473–1511. https://doi.org/10.1086/681254
Dennis, J. (2020). A party within a party posing as a movement? Momentum as a movement faction. Journal of Information Technology & Politics, 17(2), 97–113. https://doi.org/10.1080/19331681.2019.1702608
Deringer, W. (2018). Calculated values: Finance, politics, and the quantitative age. Harvard University Press.
Deseriis, M. (2020). Digital movement parties: A comparative analysis of the technopolitical cultures and the participation platforms of the movimento 5 stelle and the piratenpartei. Information, Communication & Society, 23(12), 1770–1786. https://doi.org/10.1080/1369118X.2019.1631375
Dewey, J. (1927). The public and its problems. Holt Publishers.
Diakopoulos, N. (2019). Automating the news: How algorithms are rewriting the media. Harvard University Press.
Diamandis, P. H., & Kotler, S. (2020). The future is faster than you think: How converging technologies are transforming business, industries, and our lives. Simon & Schuster.
Ding, J., Chun, A., Liu, Y.-L., Han, E., Lewis, D., Gal, D., & Creemers, R. (2020). The AI powered state: China’s approach to public sector innovation. Nesta. https://apo.org.au/sites/default/files/resource-files/2020-05/apo-nid305076.pdf
Doerr, J. (2018). Measure what matters: How Google, Bono, and the Gates Foundation rock the world with OKRs. Portfolio/Penguin.
Dommett, K. (2020). Roadblocks to interactive digital adoption? Elite perspectives of party practices in the united kingdom. Party Politics, 26(2), 165–175. https://doi.org/10.1177/1354068818761196
Dommett, K., Kefford, G., & Kruschinski, S. (2024). Data-driven campaigning and political parties: Five advanced democracies compared. Oxford University Press. https://doi.org/10.1093/oso/9780197570227.001.0001
Dommett, K., Temple, L., & Seyd, P. (2021). Dynamics of intra-party organisation in the digital age: A grassroots analysis of digital adoption. Parliamentary Affairs, 74(2), 378–397. https://doi.org/10.1093/pa/gsaa007
Donovan, J., Dreyfuss, E., & Friedberg, B. (2022). Meme wars: The untold story of the online battles upending democracy in America. Bloomsbury Publishing.
Douek, E. (2021). Governing online speech: From “posts-as-trumps” to proportionality and probability. Columbia Law Review, 121(3), 759–834. https://doi.org/10.2139/ssrn.3679607
Drezner, D. W., Farrell, H., & Newman, A. L. (2021). The uses and abuses of weaponized interdependence (D. W. Drezner, H. Farrell, & A. L. Newman, Eds.). Brookings Institution Press.
Duff, B. E., & Meisner, C. (2023). Platform governance at the margins: Social media creators’ experiences with algorithmic (in)visibility. Media, Culture & Society, 45(2), 285–304. https://doi.org/.o0r.g1/107.711/0717/6031464343473272121111923
Easley, D., & Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press. https://doi.org/10.1017/CBO9780511761942
Eldridge, S. A. (2018). Online journalism from the periphery: Interloper media and the journalistic field. Routledge. https://doi.org/10.4324/9781315671413
Elster, J. (2015). Explaining social behavior: More nuts and bolts for the social sciences (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9781107763111 (Original work published 2007)
Enos, R. D., & Hersh, E. D. (2015). Party activists as campaign advertisers: The ground campaign as a principal-agent problem. American Political Science Review, 109(2), 252–278. https://doi.org/10.1017/S0003055415000064
Entman, R. M. (2004). Projections of power: Framing news, public opinion, and U.S. Foreign policy. The University of Chicago Press.
Epstein, B., & Broxmeyer, J. D. (2020). The (surprisingly interesting) story of e-mail in the 2016 presidential election. Journal of Information Technology & Politics, 17(3), 232–248. https://doi.org/10.1080/19331681.2020.1755762
Epstein, E. J. (2017). How america lost its secrets: Edward snowden, the man and the theft. Alfred A. Knopf.
Epstein, J. M. (2006). Generative social science: Studies in agent-based computational modeling. Princeton University Press.
Erie, M. S., & Streinz, T. (2021). The beijing effect: China’s digital silk road as transnational data governance. Journal of International Law and Politics, 54(1), 1–92.
Espeland, W. N., & Sauder, M. (2007). Rankings and reactivity: How public measures recreate social worlds. American Journal of Sociology, 113(1), 1–40. https://doi.org/10.1086/517897
Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press.
Evans, B. (2020). News by the ton: 75 years of US advertising. Benedict Evans. https://www.ben-evans.com/benedictevans/2020/6/14/75-years-of-us-advertising
Evans, D. S., & Schmalensee, R. (2016). Matchmakers: The new economics of multisided platforms. Harvard Business School Publishing.
FAIR, M. F. A. R. D. T., Bakhtin, A., Brown, N., Dinan, E., Farina, G., Flaherty, C., Fried, D., Goff, A., Gray, J., Hu, H., Jacob, A. P., Komeili, M., Konath, K., Kwon, M., Lerer, A., Lewis, M., Miller, A. H., Mitts, S., Renduchintala, A., … Zijlstra, M. (2022). Human-level play in the game of Diplomacy by combining language models with strategic reasoning. Science, 378(6624), 1067–1074. https://doi.org/10.1126/science.ade9097
Fannin, R. A. (2019). Tech titans of china: How china’s tech sector is challenging the world by innovating faster, working harder & going global. Nicholas Brealey Publishing.
Farrell, H., & Newman, A. L. (2019a). Of privacy and power: The transatlantic struggle over freedom and security. Princeton University Press.
Farrell, H., & Newman, A. L. (2019b). Weaponized interdependence: How global economic networks shape state coercion. International Security, 44(1), 42–79. https://doi.org/10.1162/isec_a_00351
Farrell, H., Newman, A. L., & Wallace, J. (2022). Spirals of delusion: How AI distorts decision-making and makes dictators more dangerous. Foreign Affairs, 101(5), 168–181.
Ferguson, A. G. (2017). The rise of big data policing: Surveillance, race, and the future of law enforcement. New York University Press.
Ferree, M. M., Gamson, W. A., Gerhards, J., & Rucht, D. (2002a). Four models of the public sphere in modern democracies. Theory and Society, 31(3), 289–324. https://doi.org/10.1023/A:1016284431021
Ferree, M. M., Gamson, W. A., Gerhards, J., & Rucht, D. (2002b). Shaping abortion discourse: Democracy and the public sphere in germany and the united states. Cambridge University Press. https://doi.org/10.1017/CBO9780511613685
Filgueiras, F. (2022). The politics of AI: Democracy and authoritarianism in developing countries. Journal of Information Technology & Politics, 19(4), 449–464. https://doi.org/10.1080/19331681.2021.2016543
Flaxman, S., Goel, S., & Rao, J. M. (2016). Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(1), 298–320. https://doi.org/10.1093/poq/nfw006
Floreano, D., & Wood, R. J. (2015). Science, technology and the future of small autonomous drones. Nature, 521, 460–466. https://doi.org/10.1038/nature14542
Flyvbjerk, B. (2001). Making social science matter: Why social inquiry fails and how it can succeed again. Cambridge University Press. https://doi.org/10.1017/CBO9780511810503
Foos, F. (2024). The use of AI by election campaigns. OSF Preprints. https://doi.org/10.31219/osf.io/zm2r6
Foucault, M. (1994). The order of things: An archaeology of the human sciences (A. Sheridan, Trans.). Vintage Books. (Original work published 1966)
Fraser, N. (1990). Rethinking the public sphere: A contribution to the critique of actually existing democracy. Social Text, 25/26, 56–80. https://doi.org/10.2307/466240
Frenkel, S., & Kang, C. (2021). An ugly truth: Inside facebook’s battle for domination. Harper.
Frey, C. B. (2019). Technology trap: Capital, labor, and power in the age of automation. Princeton University Press.
Frey, M. (2021). Netflix recommends: Algorithms, film choice, and the history of taste. University of California Press.
Friedman, B., & Nissenbaum, H. (1996). Bias in computer systems. ACM Transactions on Information Systems, 14(3), 330–347. https://doi.org/10.1145/230538.230561
Frier, S. (2020). No filter: The inside story of Instagram. Simon & Schuster.
Gaisbauer, F., Pournaki, A., Banisch, S., & Olbrich, E. (2021). Ideological differences in engagement in public debate on twitter. PLoS One, 16(3), e0249241. https://doi.org/10.1371/journal.pone.0249241
Gallego, A., & Kurer, T. (2022). Automation, digitalization, and artificial intelligence in the workplace: Implications for political behavior. Annual Review of Political Science, 25, 463–484. https://doi.org/10.1146/annurev-polisci-051120-104535
Galloway, S. (2017). The four: The hidden DNA of amazon, apple, facebook, and google. Portfolio/Penguin.
Gellman, B. (2020). Dark mirror: Edward Snowden and the surveillance state. Bodley Head.
Gentzkow, M., Kelly, B., & Taddy, M. (2019). Text as data. Journal of Economic Literature, 57(3), 535–574. https://doi.org/10.1257/jel.20181020
Gentzkow, M., & Shapiro, J. M. (2011). Ideological segregation online and offline. The Quarterly Journal of Economics, 126(4), 1799–1839. https://doi.org/10.1093/qje/qjr044
Gerbaudo, P. (2019). The digital party: Political organisation and online democracy. Pluto Press.
Gerring, J. (2012). Social science methodology: A unified framework (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9781139022224 (Original work published 2001)
Gessen, M. (2020). Why are some journalists afraid of "moral clarity"? The New Yorker. https://www.newyorker.com/news/our-columnists/why-are-some-journalists-afraid-of-moral-clarity
Gessler, T., & Hunger, S. (2022). How the refugee crisis and radical right parties shape party competition on immigration. Political Science Research and Methods, 10(3), 524–544. https://doi.org/10.1017/psrm.2021.64
Gieryn, T. F. (1999). Cultural boundaries of science: Credibility on the line. University of Chicago Press.
Gigerenzer, G. (2018). The bias bias in behavioral economics. Review of Behavioral Economics, 5(3–4), 303–336. https://doi.org/10.1561/105.00000092
Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451–482. https://doi.org/10.1146/annurev-psych-120709-145346
Gilardi, F., Baumgartner, L., Dermont, C., Donnay, K., Gessler, T., Kubli, M., Leemann, L., & Müller, S. (2022). Building research infrastructures to study digital technology and politics: Lessons from Switzerland. PS: Political Science & Politics, 55(2), 354–359. https://doi.org/10.1017/S1049096521000895
Gilardi, F., Gessler, T., Kubli, M., & Müller, S. (2021). Social media and political agenda setting. Political Communication, 39(1), 39–60. https://doi.org/10.1080/10584609.2021.1910390
Golder, S. A., & Macy, M. W. (2014). Digital footprints: Opportunities and challenges for online social research. Annual Review of Sociology, 40, 129–152. https://doi.org/10.1146/annurev-soc-071913-043145
Goldfarb, A., & Lindsay, J. R. (2022). Prediction and judgment: Why artificial intelligence increases the importance of humans in war. International Security, 46(3), 7–50. https://doi.org/10.1162/isec_a_00425
Golebiewski, M., & boyd, danah. (2019). Data voids: Where missing data can easily be exploited. Data & Society. https://datasociety.net/wp-content/uploads/2019/11/Data-Voids-2.0-Final.pdf
González-Bailón, S. (2017). Decoding the social world: Data science and the unintended consequences of communication. The MIT Press.
González-Bailón, S., Borge-Holthoefer, J., Rivero, A., & Moreno, Y. (2011). The dynamics of protest recruitment through an online network. Nature Scientific Reports, 1(197). https://doi.org/10.1038/srep00197
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. The MIT Press.
Goodhart, D. (2017). The road to somewhere: The new tribes shaping british politics. C. Hurst & Co.
Gorwa, R. (2019a). The platform governance triangle: Conceptualising the informal regulation of online content. Internet Policy Review, 8(2), 1–22. https://doi.org/10.14763/2019.2.1407
Gorwa, R. (2019b). What is platform governance? Information, Communication & Society, 22(6), 854–871. https://doi.org/10.1080/1369118X.2019.1573914
Gorwa, R., Binns, R., & Katzenbach, C. (2020). Algorithmic content moderation: Technical and political challenges in the automation of platform governance. Big Data & Society, 7(1), 1–15. https://doi.org/10.1177/2053951719897945
Granovetter, M. (2017). Society and economy: Framework and principles. The Belknap Press of Harvard University.
Green, J. (2017). Devil’s bargain: Steve Bannon, Donald Trump, and the storming of the Presidency. Penguin Press.
Gregory, P. R., & Markevich, A. (2002). Creating Soviet industry: The house that Stalin built. Slavic Review, 61(4), 787–814. https://doi.org/10.2307/3090390
Griffiths, J. (2019). The great firewall of China: How to build and control an alternative version of the internet. ZED Books.
Grimmer, J., Roberts, M. E., & Stewart, B. M. (2022). Text as data: A new framework for machine learning and the social sciences. Princeton University Press.
Guess, A. M., Nyhan, B., & Reifler, J. (2020). Exposure to untrustworthy websites in the 2016 US election. Nature Human Behavior, 4, 472–480. https://doi.org/10.1038/s41562-020-0833-x
Guess, A., Nagler, J., & Tucker, J. A. (2019). Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Science Advances, 5(1), 1–8. https://doi.org/10.1126/sciadv.aau4586
Guess, A., Nyhan, B., Lyons, B., & Reifler, J. (2018). Avoiding the echo chamber about echo chambers: Why selective exposure to like-minded political news is less prevalent than you think. Knight Foundation. {https://kf-site-production.s3.amazonaws.com/media_elements/files/000/000/133/original/Topos_KF_White-Paper_Nyhan_V1.pdf}
Gurri, M. (2018). The revolt of the public and the crisis of authority in the new millennium (2nd ed.). Stripe Press.
Guttman, A. (2007). Democracy. In R. E. Goodin, P. Pettit, & T. Pogge (Eds.), A companion to contemporary political philosophy (2nd ed., pp. 521–532). Blackwell Publishing. https://doi.org/10.1002/9781405177245.ch25
Habermas, J. (1981). Theorie des kommunikativen Handelns. Suhrkamp.
Habermas, J. (1990). Strukturwandel der Öffentlichkeit: Untersuchungen zu einer Kategorie der bürgerlichen Gesellschaft. Suhrkamp. (Original work published 1962)
Hafner, K., & Lyon, M. (1996). Where wizards stay up late: The origins of the internet. Simon & Schuster.
Halberstam, D. (1972). The best and the brightest. Random House.
Han, H. (2014). How organizations develop activists: Civic associations and leadership in the 21st century. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199336760.001.0001
Hand, D. J. (2004). Measurement theory and practice: The world through quantification. Wiley.
Hand, D. J. (2007). Information generation: How data rule our world. Oneworld.
Hand, D. J., Mannila, H., & Smyth, P. (2001). Principles of data mining. The MIT Press.
Hanna, R. N., & Linden, L. L. (2012). Discrimination in grading. American Economic Journal: Economic Policy, 4(4), 146–168. https://doi.org/10.1257/pol.4.4.146
Hanson, R. (2016). The age of Em: Work, love, and life when robots rule the earth. Oxford University Press. https://doi.org/10.1093/oso/9780198754626.001.0001
Harcourt, B. E. (2006). Against prediction: Profiling, policing, and punishing in an actuarial age. University of Chicago Press.
Hardt, H. (2001). Social theories of the press: Constituents of communication research, 1840s to 1920s (2nd ed.). Rowman & Littlefield.
Harwell, D., & Lorenz, T. (2023). Israel-Gaza war sparks debate over TikTok’s role in setting public opinion. Washington Post. https://www.washingtonpost.com/technology/2023/11/02/tiktok-israel-hamas-video-brainwash/
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). Springer. https://doi.org/10.1007/978-0-387-84858-7 (Original work published 2001)
Herbst, S. (1993). Numbered voices: How opinion polling has shaped american politics. The University of Chicago Press.
Hersh, E. D. (2015). Hacking the electorate: How campaigns perceive voters. Cambridge University Press. https://doi.org/10.1017/CBO9781316212783
Hersh, E. D. (2018). Cambridge Analytica and the future of data privacy: Written testimony of Eitan Hersh. In Hearing before the United States Senate Committee on the Judiciary. United States Senate. https://www.judiciary.senate.gov/imo/media/doc/05-16-18%20Hersh%20Testimony1.pdf
Hesse, H. (2002). The glass bead game (R. Winston & C. Winston, Trans.). Picador. (Original work published 1943)
Hillman, J. E. (2021). The digital silk road: China’s quest to wire the world and win the future. Harper Business.
Hindman, M. (2005). The real lessons of Howard Dean: Reflections on the first digital campaign. Perspectives on Politics, 3(1), 121–128. https://doi.org/10.1017/S1537592705050115
Hindman, M. (2009). The myth of of digital democracy. Princeton University Press.
Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50–68. https://doi.org/10.1177/002224299606000304
Hoffmann, C. P. (2020). Techlash: Digitale plattformen zwischen utopie und dystopie. In S. Russ-Mohl (Ed.), Streitlust und streitkunst: Diskurs als essenz der demokratie (pp. 66–91). Herbert von Halem Verlag.
Hofman, J. M., Sharma, A., & Watts, D. J. (2017). Prediction and explanation in social systems. Science, 355(6324), 486–488. https://doi.org/10.1126/science.aal3856
Holmberg, E. S. (2021). Lessons from Trump’s suspension: How Twitter should clarify and strengthen its “public interest” approach to moderating leaders’ violence-inspiring speech. Harvard Journal of Law & Technology, 35(1).
Holmes, D. E. (2017). Big data: A very short introduction. Oxford University Press.
Horton, J. J. (2023). Large language models as simulated economic agents: What can we learn from Homo Silicus? NBER Working Papers. https://doi.org/10.3386/w31122
Howison, J., Wiggins, A., & Crowston, K. (2011). Validity issues in the use of social network analysis with digital trace data. Journal of the Association for Information Systems, 12(12), 767–797. https://doi.org/10.17705/1jais.00282
Hvitfeldt, E. (2022). Supervised machine learning for text analysis in r. CRC Press.
Hwang, T. (2020). Subprime attention crisis: Advertising and the time bomb at the heart of the internet. Farrat, Straus; Giroux.
Igo, S. (2007). The averaged american: Surveys, citizens, and the making of a mass public. Harvard University Press.
Igo, S. E. (2018). The known citizen: A history of privacy in modern america. Harvard University Press.
IJzerman, H., Lewis Jr., N. A., Przybylski, A. K., Weinstein, N., DeBruine, L., Ritchie, S. J., Vazire, S., Forscher, P. S., Morey, R. D., Ivory, J. D., & Anvari, F. (2020). Use caution when applying behavioural science to policy. Nature Human Behavior, 4, 1092–1094. https://doi.org/10.1038/s41562-020-00990-w
Imbens, G. W., & Rubin, D. B. (2015). Causal inference for statistics, social, and biomedical sciences: An introduction. Cambridge University Press.
Isaac, M. (2019). Super pumped: The battle for uber. W. W. Norton & Company.
Isaacson, W. (2014). The innovators: How a group of inventors, hackers, geniuses, and geeks created the digital revolution. Simon & Schuster.
Issenberg, S. (2012). The victory lab: The secret science of winning campaigns. Crown Publishing Group.
Iyer, R., Koleva, S., Graham, J., Ditto, P., & Haidt, J. (2012). Understanding libertarian morality: The psychological dispositions of self-identified Libertarians. PLoS One, 7(8), e42366. https://doi.org/10.1371/journal.pone.0042366
Jackson, S. J., Bailey, M., & Welles, B. F. (2020). #HashtagActivism: Networks of race and gender justice. The MIT Press.
Jiang, M., & Fu, K. (2018). Chinese social media and big data: Big data, big brother, big profit? Policy & Internet, 10(4), 372–392. https://doi.org/10.1002/poi3.187
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žı́dek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S. A. A., Ballard, A. J., Cowie, A., Romera-Paredes, B., Nikolov, S., Jain, R., Adler, J., … Hassabis, D. (2021). Highly accurate protein structure prediction with AlphaFold. Nature, 596(7873), 583–589. https://doi.org/10.1038/s41586-021-03819-2
Jungherr, A. (2012). The German federal election of 2009: The challenge of participatory cultures in political campaigns. Transformative Works and Cultures, 10. https://doi.org/10.3983/twc.2012.0310
Jungherr, A. (2014). The logic of political coverage on Twitter: Temporal dynamics and content. Journal of Communication, 64(2), 239–259. https://doi.org/10.1111/jcom.12087
Jungherr, A. (2015). Analyzing political communication with digital trace data: The role of twitter messages in social science research. Springer. https://doi.org/10.1007/978-3-319-20319-5
Jungherr, A. (2016a). Datengestützte Verfahren im Wahlkampf. Zeitschrift für Politikberatung, 8(1), 3–14. https://doi.org/10.5771/1865-4789-2016-1-3
Jungherr, A. (2016b). Four functions of digital tools in election campaigns: The German case. The International Journal of Press/Politics, 21(3), 358–377. https://doi.org/10.1177/1940161216642597
Jungherr, A. (2019). Normalizing digital trace data. In N. J. Stroud & S. C. McGregor (Eds.), Digital discussions: How big data informs political communication (pp. 9–35). Routledge. https://doi.org/10.4324/9781351209434-2
Jungherr, A. (2023a). Artificial intelligence and democracy: A conceptual framework. Social Media + Society, 9(3), 1–14. https://doi.org/10.1177/20563051231186353
Jungherr, A. (2023b). Digital campaigning: How digital media change the work of parties and campaign organizations and impact elections. In J. Skopek (Ed.), Research handbook digital sociology (pp. 446–462). Edward Elgar. https://doi.org/10.4337/9781789906769.00035
Jungherr, A., & Jürgens, P. (2010). The political click: Political participation through e-petitions in Germany. Policy & Internet, 2(4), 131–165. https://doi.org/10.2202/1944-2866.1084
Jungherr, A., & Jürgens, P. (2013). Forecasting the pulse: How deviations from regular patterns in online data can identify offline phenomena. Internet Research, 23(5), 589–607. https://doi.org/10.1108/IntR-06-2012-0115
Jungherr, A., & Jürgens, P. (2014). Through a glass, darkly: Tactical support and symbolic association in Twitter messages commenting on Stuttgart 21. Social Science Computer Review, 32(1), 74–89. https://doi.org/10.1177/0894439313500022
Jungherr, A., Posegga, O., & An, J. (2019). Discursive power in contemporary media systems: A comparative framework. The International Journal of Press/Politics, 24(4), 404–425. https://doi.org/10.1177/1940161219841543
Jungherr, A., Posegga, O., & An, J. (2022). Populist supporters on Reddit: A comparison of content and behavioral patterns within publics of supporters of Donald Trump and Hillary Clinton. Social Science Computer Review, 40(3), 809–830. https://doi.org/10.1177/0894439321996130
Jungherr, A., & Rauchfleisch, A. (2024). Negative downstream effects of alarmist disinformation discourse: Evidence from the United States. Political Behavior, 1–21. https://doi.org/10.1007/s11109-024-09911-3
Jungherr, A., Rauchfleisch, A., & Wuttke, A. (2024). Deceptive uses of Artificial Intelligence in elections strengthen support for AI ban. arXiv. https://doi.org/10.48550/arXiv.2408.1261
Jungherr, A., Rivero, G., & Gayo-Avello, D. (2020). Retooling politics: How digital media are shaping democracy. Cambridge University Press. https://doi.org/10.1017/9781108297820
Jungherr, A., & Schlarb, D. (2022). The extended reach of game engine companies: How companies like Epic Games and Unity Technologies provide platforms for extended reality applications and the metaverse. Social Media + Society, 8(2), 1–12. https://doi.org/10.1177/20563051221107641
Jungherr, A., Schoen, H., & Jürgens, P. (2016). The mediation of politics through Twitter: An analysis of messages posted during the campaign for the German federal election 2013. Journal of Computer-Mediated Communication, 21(1), 50–68. https://doi.org/10.1111/jcc4.12143
Jungherr, A., Schoen, H., Posegga, O., & Jürgens, P. (2017). Digital trace data in the study of public opinion: An indicator of attention toward politics rather than political support. Social Science Computer Review, 35(3), 336–356. https://doi.org/10.1177/0894439316631043
Jungherr, A., & Schroeder, R. (2021). Disinformation and the structural transformations of the public arena: Addressing the actual challenges to democracy. Social Media + Society, 7(1), 1–13. https://doi.org/10.1177/2056305121988928
Jungherr, A., & Schroeder, R. (2022). Digital transformations of the public arena. Cambridge University Press. https://doi.org/10.1017/9781009064484
Jungherr, A., & Schroeder, R. (2023). Artificial intelligence and the public arena. Communication Theory, 33(2–3), 164–173. https://doi.org/10.1093/ct/qtad006
Jungherr, A., Schroeder, R., & Stier, S. (2019). Digital media and the surge of political outsiders: Explaining the success of political challengers in the United States, Germany, and China. Social Media + Society, 5(3), 1–12. https://doi.org/10.1177/2056305119875439
Jungherr, A., & Theocharis, Y. (2017). The empiricist’s challenge: Asking meaningful questions in political science in the age of big data. Journal of Information Technology & Politics, 14(1), 97–109. https://doi.org/10.1080/19331681.2017.1312187
Jungherr, A., Wuttke, A., Mader, M., & Schoen, H. (2021). A source like any other? Field and survey experiment evidence on how interest groups shape public opinion. Journal of Communication, 71(2), 276–304. https://doi.org/10.1093/joc/jqab005
Jürgens, P., Jungherr, A., & Schoen, H. (2011). Small worlds with a difference: New gatekeepers and the filtering of political information on Twitter. In D. D. Roure & S. Poole (Eds.), WebSci 2011: Proceedings of the 3rd international web science conference. ACM. https://doi.org/10.1145/2527031.2527034
Jürgens, P., Meltzer, C. E., & Scharkow, M. (2022). Age and gender representation on German TV: A longitudinal computational analysis. Computational Communication Science, 4(1). https://doi.org/10.5117/CCR2022.1.005.JURG
Jürgens, P., & Stark, B. (2017). The power of default on Reddit: A general model to measure the influence of information intermediaries. Policy & Internet, 9(4), 395–419. https://doi.org/10.1002/poi3.166
Jürgens, P., Stark, B., & Magin, M. (2020). Two half-truths make a whole? On bias in self-reports and tracking data. Social Science Computer Review, 38(5), 600–615. https://doi.org/10.1177/0894439319831643
Kafka, F. (1998). The castle (M. Harman, Trans.). Schocken. (Original work published 1926)
Kafka, F. (1999). The trial (B. Mitchell, Ed. & Trans.). Schocken. (Original work published 1925)
Kahan, D. M. (2016a). The politically motivated reasoning paradigm, part 1: What politically motivated reasoning is and how to measure it. In R. A. Scott & M. C. Buchmann (Eds.), Emerging Trends in the Social and Behavioral Sciences (pp. 1–16). John Wiley & Sons. https://doi.org/10.1002/9781118900772.etrds0417
Kahan, D. M. (2016b). The politically motivated reasoning paradigm, part 2: Unanswered questions. In R. A. Scott & M. C. Buchmann (Eds.), Emerging Trends in the Social and Behavioral Sciences (pp. 1–15). John Wiley & Sons. https://doi.org/10.1002/9781118900772.etrds0418
Kaiser, J., & Rauchfleisch, A. (2019). The implications of venturing down the rabbit hole. Internet Policy Review. https://policyreview.info/articles/news/implications-venturing-down-rabbit-hole/1406
Kaiser, J., & Rauchfleisch, A. (2020). Birds of a feather get recommended together: Algorithmic homophily in YouTube’s channel recommendations in the United States and Germany. Social Media + Society, 6(4), 1–15. https://doi.org/10.1177/2056305120969914
Kanno-Young, Z., & Kang, C. (2021). They’re killing people”: Biden denounces social media for virus disinformation. The New York Times. https://www.nytimes.com/2021/07/16/us/politics/biden-facebook-social-media-covid.html
Kapczynski, A. (2020). The law of informational capitalism. The Yale Law Journal, 129(5), 1460–1515.
Kargar, S., & Rauchfleisch, A. (2019). State-aligned trolling in Iran and the double-edged affordances of Instagram. New Media & Society, 21(7), 1506–1527. https://doi.org/10.1177/1461444818825133
Karpf, D. (2012a). Social science research methods in internet time. Information, Communication & Society, 15(5), 639–661. https://doi.org/10.1080/1369118X.2012.665468
Karpf, D. (2012b). The MoveOn effect: The unexpected transformation of american political advocacy. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199898367.001.0001
Karpf, D. (2016). Analytical activism: Digital listerning and the new political strategy. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780190266127.001.0001
Karpf, D. (2019). Something I no longer believe: Is internet time slowing down? Social Media + Society, 5(3), 1–4. https://doi.org/10.1177/2056305119849492
Katz, E., & Lazarsfeld, P. F. (1955). Personal influence, the part played by people in the flow of mass communications. The Free Press.
Katz, R. S., & Mair, P. (2018). Democracy and the cartelization of political parties. Oxford University Press.
Kaye, D. (2018). Report on artificial intelligence technologies and implications for freedom of expression and the information environment. United Nations Human Rights Office of the High Commissioner. https://www.ohchr.org/EN/Issues/FreedomOpinion/Pages/ReportGA73.aspx
Kaye, D. (2019). Speech police: The global struggle to govern the internet. Columbia Global Reports.
Keane, J. (2013). Democracy and media decadence. Cambridge University Press. https://doi.org/10.1017/CBO9781107300767
Kelleher, J. D. (2019). Deep learning. The MIT Press.
Keller, D. (2018). Internet platforms: Observations on speech, danger, and money. Hoover Institution. https://cyberlaw.stanford.edu/files/publication/files/381732092-internet-platforms-observations-on-speech-danger-and-money.pdf
Keuschnigg, M., Lovsjö, N., & Hedström, P. (2018). Analytical sociology and computational social science. Journal of Computational Social Science, 1(1), 3–14. https://doi.org/10.1007/s42001-017-0006-5
Kiefer, M. L. (2010). Journalismus und Medien als Institutionen. UVK Verlagsgesellschaft.
Kim, H., Choi, H., Kang, H., An, J., Yeom, S., & Hong, T. (2021). A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities. Renewable and Sustainable Energy Reviews, 140(110755), 1–17. https://doi.org/10.1016/j.rser.2021.110755
Kim, J., & Lee, B. (2023). AI-augmented surveys: Leveraging large language models for opinion prediction in nationally representative surveys. arXiv. https://doi.org/10.48550/arXiv.2305.09620
King, G. (2011). Ensuring the data-rich future of the social sciences. Science, 331(6018), 719–721. https://doi.org/10.1126/science.1197872
King, R. D., Rowland, J., Oliver, S. G., Young, M., Aubrey, W., Byrne, E., Liakata, M., Markham, M., Pir, P., Soldatova, L. N., Sparkes, A., Whelan, K. E., Whelan, K. E., & Clare, A. (2009). The automation of science. Science, 324(5923), 88–89. https://doi.org/10.1126/science.1165620
Kitchens, B., Johnson, S. L., & Gray, P. (2020). Understanding echo chambers and filter bubbles: The impact of social media on diversification and partisan shifts in news consumption. MIS Quarterly, 44(4), 1619–1649. https://doi.org/10.25300/MISQ/2020/16371
Kitchin, R. (2014). Big data, new epistemologies and paradigm shifts. Big Data & Society, 1(1), 1–12. https://doi.org/10.1177/2053951714528481
Kleinberg, J., & Tardos, Éva. (2005). Algorithm design. Addison Wesley Longman.
Knight, A., & Creemers, R. (2021). Going viral: The Social Credit System and COVID-19. Social Science Research Network. https://doi.org/10.2139/ssrn.3770208
Knockel, J., Parsons, C., Ruan, L., Xiong, R., Crandall, J., & Deibert, R. (2020). We chat, they watch how international users unwittingly build up WeChat’s chinese censorship apparatus. The Citizen Lab. https://tspace.library.utoronto.ca/bitstream/1807/101395/1/Report%23127--wechattheywatch-web.pdf
Knüpfer, C., Hoffmann, M., & Voskrensenskii, V. (2022). Hijacking MeToo: Transnational dynamics and networked frame contestation on the far right in the case of the “120 decibels” campaign. Information, Communication & Society, 25(7), 1010–1028. https://doi.org/10.1080/1369118X.2020.1822904
Knuth, D. E. (1997). The art of computer programming: Fundamental algorithms (3rd ed., Vol. 1). Addison Wesley Longman. (Original work published 1968)
Kovach, B., & Rosenstiel, T. (2021). The elements of journalism: What newspeople should know and the public should expect (4th ed.). The Crown Publishing Group. (Original work published 2001)
Krebs, S., McCain, R. M., & Brundage, M. (2022). All the news that’s fit to fabricate: AI-generated text as a tool of media misinformation. Journal of Experimental Political Science, 9(1), 104–117. https://doi.org/10.1017/XPS.2020.37
Kreiss, D. (2012). Taking our country back: The crafting of networked politics from Howard Dean to Barack Obama. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199782536.001.0001
Kreiss, D. (2016). Prototype politics: Technology-intensive campaigning and the data of democracy. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199350247.001.0001
Kreiss, D. (2019). Digital opportunity structures: Explaining variation in digital mobilization during the 2016 democratic primaries. In M. X. D. Carpini (Ed.), Digital media and democratic futures (pp. 42–68). University of Pennsylvania Press.
Kretschmer, M., Kretschmer, T., Peukert, A., & Peukert, C. (2023). The risks of risk-based AI regulation: Taking liability seriously. arXiv, 1–18. https://doi.org/10.48550/arXiv.2311.14684
Kroll, A. (2018). Cloak and data: The real story behind Cambridge Analytica’s rise and fall. Mother Jones, May/June. https://www.motherjones.com/politics/2018/03/cloak-and-data-cambridge-analytica-robert-mercer/
Kuklinski, J. H., & Quirk, P. J. (2000). Reconsidering the rational public: Cognition, heuristics, and mass opinion. In A. Lupia, M. D. McCubbins, & S. L. Popkin (Eds.), Elements of reason: Cognition, choice, and the bounds of rationality (pp. 153–182). Cambridge University Press. https://doi.org/10.1017/CBO9780511805813.008
Kullback, S., & Leibler, R. A. (1951). On information and sufficiency. The Annals of Mathematical Statistics, 22(1), 79–86.
Kuran, T. (1995). Private truths, public lies: The social consequences of preference falsification. Harvard University Press.
Lafont, C. (2020). Democracy without shortcuts: A participatory conception of deliberative democracy. Oxford University Press. https://doi.org/10.1093/oso/9780198848189.001.0001
Landemore, H. (2012). Democratic reason: Politics, collective intelligence, and the rule of the many. Princeton University Press.
Landemore, H. (2024). Can artificial intelligence bring deliberation to the masses? In R. Chang & A. Srinivasan (Eds.), Conversations in philosophy, law, and politics (pp. 39–69). Oxford University Press. https://doi.org/10.1093/oso/9780198864523.003.0003
Landemore, H., & Elster, J. (Eds.). (2012). Collective wisdom: Principles and mechanisms. Cambridge University Press. https://doi.org/10.1017/CBO9780511846427
Lane, H., & Dyshel, M. (2022). Natural language processing in action: Understanding, analyzing, and generating text with python (2nd ed.). Manning Publications Co.
Laney, D. (2001). 3D data management: Controlling data volume, velocity, and variety, application delivery strategies. META Group: Application Delivery Strategies, 949.
Lanz, M., & Precht, R. D. (2022). Lanz und Precht diskutieren über die Medienlandschaft. Lanz Und Precht. https://www.youtube.com/watch?v=OvUSVSdr-zI
Larson, E. J. (2021). The myth of artificial intelligence: Why computers can’t think the way we do. The Belknap Press of Harvard University.
Laswell, H. (1948). The structure and function of communication in society. In L. Bryson (Ed.), The communication of ideas (pp. 243–276). Institue for Religous; Social Studies.
Laver, M., Benoit, K., & Garry, J. (2003). Extracting policy positions from political texts using words as data. American Political Science Review, 97(2), 311–331. https://doi.org/10.1017/S0003055403000698
Lazer, D., Kennedy, R., King, G., & Vespignani, A. (2014). The parable of Google Flu: Traps in big data analysis. Science, 343(6176), 1203–1205. https://doi.org/10.1126/science.1248506
Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M. W., Roy, D., & Alstyne, M. V. (2009). Computational social science. Science, 323(5915), 721–723. https://doi.org/10.1126/science.1167742
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539
Lee, K.-F. (2018). AI superpowers: China, Silicon Valley, and the new world order. Houghton Mifflin Harcourt.
Lee, K.-F., & Quifan, C. (2021). AI 2041: Ten visions for our future. Currency.
Lepore, J. (2020). If then: How one data company invented the future. W. W. Norton & Company.
Levine, F., Locke, C., Searls, D., & Weinberger, D. (2000). The cluetrain manifesto: The end of business as usual. Persus Publishing.
Levy, S. (2010). Hackers: Heroes of the computer revolution. O’Reilly Media.
Levy, S. (2011). In the plex: How google thinks, works, and shapes our lives. Simon & Schuster.
Levy, S. (2020). Facebook: The inside story. Blue Rider Press.
Lewis, M. (2014). Flash boys: A wall street revolt. W. W. Norton & Company.
Liang, F., Das, V., Kostyuk, N., & Hussain, M. M. (2018). Constructing a data-driven society: China’s social credit system as a state surveillance infrastructure. Policy & Internet, 10(4), 415–453. https://doi.org/10.1002/poi3.183
Lindblom, C. E. (1965). Intelligence of democracy: Decision making through mutual adjustment. The Free Press.
Lindblom, C. E. (2001). The market system: What it is, how it works, and what to make of it. Yale University Press.
Lippmann, W. (1927). The phantom public. The Macmillan Company.
Little, D. (2020). A new social ontology of government: Consent, coordination, and authority. Palgrave Macmillan. https://doi.org/10.1007/978-3-030-48923-6
Liu, X., Glocker, B., McCradden, M. M., Ghassemi, M., Denniston, A. K., & Oakden-Rayner, L. (2022). The medical algorithmic audit. The Lancet: Digital Health, 4(5), E384–E397. https://doi.org/10.1016/S2589-7500(22)00003-6
Lodge, M., & Taber, C. S. (2013). The rationalizing voter. Cambridge University Press. https://doi.org/10.1017/CBO9781139032490
Louridas, P. (2017). Real-world algorithms: A beginner’s guide. The MIT Press.
Lowe, W. (2008). Understanding Wordscores. Political Analysis, 16(4), 356–371. https://doi.org/10.1093/pan/mpn004
Lowery, W. (2020). A reckoning over objectivity, led by black journalists. The New York Times. https://www.nytimes.com/2020/06/23/opinion/objectivity-black-journalists-coronavirus.html
Lu, Y., & Pan, J. (2021). Capturing clicks: How the Chinese Government uses clickbait to compete for visibility. Political Communication, 38(1–2), 23–54. https://doi.org/10.1080/10584609.2020.1765914
Lupia, A., & McCubbins, M. D. (1998). The democratic dilemma: Can citizens learn what they need to know? Cambridge University Press.
Lutscher, P. M., Weidmann, N. B., Roberts, M. E., Jonker, M., & King, A. (2020). At home and abroad: The use of denial-of-service attacks during elections in nondemocratic regimes. Journal of Conflict Resolution, 64(2-3), 373–401. https://doi.org/10.1177/0022002719861676
MacKenzie, D. (2021). Trading at the speed of light: How ultrafast algorithms are transforming financial markets. Princeton University Press.
MacKenzie, D. (2022). Blink, bid, buy. London Review of Books, 44(9). https://www.lrb.co.uk/the-paper/v44/n09/donald-mackenzie/blink-bid-buy
MacKenzie, D., Caliskan, K., & Rommerskirchen, C. (2023). The longest second: Header bidding and the material politics of online advertising. Economy and Society, 42(3), 554–578. https://doi.org/10.1080/03085147.2023.2238463
Macy, M. W., & Willer, R. (2002). From factors to actors: Computational sociology and agent-based modeling. Annual Review of Sociology, 28, 143–166. https://doi.org/10.1146/annurev.soc.28.110601.141117
Mair, P. (2013). Ruling the void: The hollowing of Western democracy. Verso.
Margetts, H. (2001). The cyber party: The causes and consequences of organisational innovation in european political parties. In The causes and consequences of organisational innovation in european political parties. ECPR Joint Sessions of Workshops.
Margetts, H. (2006). Cyber parties. In R. S. Katz & W. Crotty (Eds.), Handbook of party politics (pp. 528–535). SAGE. https://doi.org/10.4135/9781848608047.n46
Mau, S. (2019). The metric society: On the quantification of the social (S. Howe, Trans.). Polity Press. (Original work published 2017)
Mayson, S. G. (2019). Bias in, bias out. The Yale Law Journal, 128(8), 2218–2300.
McCombs, M., & Valenzuela, S. (2021). Setting the agenda: Mass media and public opinion (3rd ed.). Polity Press. (Original work published 2004)
McCorduck, P. (2004). Machines who think: A personal inquiry into the history and prospects of artificial intelligence. A K Peters.
McElreath, R. (2020). Statistical rethinking: A bayesian course with examples in r and stan (2nd ed.). CRC Press.
McFarland, M. (2014). Elon Musk: ’With artificial intelligence we are summoning the demon.’. The Washington Post. https://doi.org/2014-10-24
McGregor, S. C. (2019). Social media as public opinion: How journalists use social media to represent public opinion. Journalism, 20(8), 1070–1086. https://doi.org/10.1177/1464884919845458
McGregor, S. C. (2020). Taking the temperature of the room”: How political campaigns use social media to understand and represent public opinion. Public Opinion Quarterly, 84(S1), 236–256. https://doi.org/10.1093/poq/nfaa012
McKenna, E., & Han, H. (2014). Groundbreakers: How Obama’s 2.2 Million volunteers transformed campaigning in America. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199394593.001.0001
McQuail, D. (2013). Journalism and society. SAGE Publications.
Meckler, L. (2012). Obama data trove is up for grabs. The Wall Street Journal. https://www.wsj.com/articles/SB10001424127887323622904578129432544571720
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2022). A survey on bias and fairness in machine learning. ACM Computing Surveys, 54(6), 1–35. https://doi.org/10.1145/3457607
Menkveld, A. J. (2016). The economics of high-frequency trading: Taking stock. Annual Review of Financial Economics, 8, 1–24. https://doi.org/10.1146/annurev-financial-121415-033010
Mennicken, A., & Espeland, W. N. (2019). What’s new with numbers? Sociological approaches to the study of quantification. Annual Review of Sociology, 35, 223–245. https://doi.org/10.1146/annurev-soc-073117-041343
Mercier, H. (2020). Not born yesterday: The science of who we trust and what we believe. Princeton University Press.
Merz, N., Regel, S., & Lewandowski, J. (2016). The Manifesto Corpus: A new resource for research on political parties and quantitative text analysis. Research & Politics, 3(2), 1–8. https://doi.org/10.1177/2053168016643346
Metaxa, D., Park, J. S., Robertson, R., Karahalios, K., Wilson, C., Hancock, J., & Sandvig, C. (2021). Auditing algorithms: Understanding algorithmic systems from the outside in. Foundations and Trends in Human–Computer Interaction, 14(4), 272–344. https://doi.org/10.1561/1100000083
Metz, C. (2021). Genius makers: The mavericks who brought AI to Google, Facebook, and the world. Dutton.
Mignano, M. (2022). The end of social media and the rise of recommendation media. Every. https://doi.org/https://every.to/p/the-end-of-social-media
Miller, J. H., & Page, S. E. (2007). Complex adaptive systems: An introduction to computational models of social life. Princeton University Press.
Mitchell, M. (2019). Artificial intelligence: A guide for thinking humans. Farrat, Straus; Giroux.
Mitchell, S., Potash, E., Barocas, S., D’Amour, A., & Lum, K. (2021). Algorithmic fairness: Choices, assumptions, and definitions. Annual Review of Statistics and Its Application, 8, 141–163. https://doi.org/10.1146/annurev-statistics-042720-125902
Möller, J., Trilling, D., Helberger, N., & van Es, B. (2018). Do not blame it on the algorithm: An empirical assessment of multiple recommender systems and their impact on content diversity. Information, Communication & Society, 21(7), 959–977. https://doi.org/10.1080/1369118X.2018.1444076
Morgan, S. L., & Winship, C. (2015). Counterfactuals and causal inference: Methods and principles for social research (2nd ed.). Cambridge University Press.
Morgus, R. (2019). The spread of russia’s digital authoritarianism. In N. D. Wright (Ed.), Artificial intelligence, china, russia, and the global order: Technological, political, global, and creative perspectives (pp. 89–97). Air University Press.
Mozur, P., Xiao, M., & Liu, J. (2022). “An invisible cage”: How China is policing the future. The New York Times. https://www.nytimes.com/2022/06/25/technology/china-surveillance-police.html
Muller, J. Z. (2018). The tyranny of metrics. Princeton University Press.
Müller, J.-W. (2021). Democracy rules. Allen Lane.
Müller, S. (2022). The temporal focus of campaign communication. The Journal of Politics, 84(1), 585–590. https://doi.org/10.1086/715165
Munger, K. (2017). Tweetment effects on the tweeted: Experimentally reducing racist harassment. Political Behavior, 39(3), 629–649. https://doi.org/10.1007/s11109-016-9373-5
Munger, K., & Phillips, J. (2022). Right-wing YouTube: A supply and demand perspective. The International Journal of Press/Politics, 27(1), 186–219. https://doi.org/10.1177/1940161220964767
Murgia, M. (2023). Algorithms are deciding who gets organ transplants. Are their decisions fair? Financial Times. https://www.ft.com/content/5125c83a-b82b-40c5-8b35-99579e087951
Narayanan, A. (2023). Understanding social media recommendation algorithms. Knight First Amendment Institute at Columbia University. https://knightcolumbia.org/content/understanding-social-media-recommendation-algorithms
Natale, S., & Ballatore, A. (2014). The web will kill them all: New media, digital utopia, and political struggle in the Italian 5-Star Movement. Media, Culture & Society, 36(1), 105–121. https://doi.org/10.1177/0163443713511902
Neuman, W. R. (1991). The future of the mass audience. Cambridge University Press.
Neuman, W. R., Guggenheim, L., Jang, S. M., & Bae, S. Y. (2014). The dynamics of public attention: Agenda-setting theory meets big data. Journal of Communication, 64(2), 193–214. https://doi.org/10.1111/jcom.12088
Newman, N., Fletcher, R., Robertson, C. T., Eddy, K., & Nielsen, R. K. (2022). Reuters institute digital news report 2022. Reuters Institute for the Study of Journalism. https://reutersinstitute.politics.ox.ac.uk/digital-news-report/2022
Nicholls, T., Shbbir, N., & Nielsen, R. K. (2016). Digital-born news media in europe. Reuters Institute for the Study of Journalism.
Nickerson, D. W., & Rogers, T. (2014). Political campaigns and big data. The Journal of Economic Perspectives, 28(2), 51–74. https://doi.org/10.1257/jep.28.2.51
Nielsen, M. (2012). Reinventing discovery: The new era of networked science. Princeton University Press.
Nielsen, R. K. (2011). Mundane internet tools, mobilizing practices, and the coproduction of citizenship in political campaigns. New Media & Society, 13(5), 755–771. https://doi.org/10.1177/1461444810380863
Nielsen, R. K. (2012). Ground wars: Personalized communication in political campaigns. Princeton University Press.
Nielsen, R. K. (2018). No one cares what we know: Three responses to the irrelevance of political communication research. Political Communication, 35(1), 145–149. https://doi.org/10.1080/10584609.2017.1406591
Nielsen, R. K. (2020). Economic contexts of journalism. In K. Wahl-Jorgensen & T. Hanitzsch (Eds.), The handbook of journalism studies (2nd ed., pp. 324–340). Routledge. https://doi.org/10.4324/9781315167497-21
Nielsen, R. K., & Fletcher, R. (2022). Concentration of online news traffic and publishers’ reliance on platform referrals: Evidence from passive tracking data in the UK. Journal of Quantitative Description: Digital Media, 2, 1–23. https://doi.org/10.51685/jqd.2022.015
Nielsen, R. K., & Ganter, S. A. (2018). Dealing with digital intermediaries: A case study of the relations between publishers and platforms. New Media & Society, 20(4), 1600–1617. https://doi.org/10.1177/1461444817701318
Nilsson, N. J. (2010). The quest for artificial intelligence: A history of ideas and achievements. Cambridge University Press. https://doi.org/10.1017/CBO9780511819346
Nissenbaum, H. (2009). Privacy in context: Technology, policy, and the integrity of social life. Stanford University Press.
Nuernbergk, C., & Conrad, J. (2016). Conversations and campaign dynamics in a hybrid media environment: Use of Twitter by members of the German Bundestag. Social Media + Society, 2(1), 1–14. https://doi.org/10.1177/2056305116628888
Nyhan, B. (2020). Facts and myths about misperceptions. Journal of Economic Perspectives, 34(3), 220–236. https://doi.org/10.1257/jep.34.3.220
O’Mara, M. (2019). The code: Silicon valley and the remaking of america. Penguin Press.
O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.
O’Reilly, T. (2005). What is Web 2.0: Design patterns and business models for the next generation of software. O’Reilly Blog. http://oreilly.com/web2/archive/what-is-web-20.html
O’Reilly, T. (2017). WTF? What’s the future and why it’s up to us. Harper Collins.
Ober, J. (2008). Democracy and knowledge: Innovation and learning in classical athens. Princeton University Press.
Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447–453. https://doi.org/10.1126/science.aax2342
Offe, C. (2006). Political institutions and social power: Conceptual explorations. In I. Shapiro, S. Skowronek, & D. Galvin (Eds.), Rethinking political institutions. The art of the state (pp. 9–31). New York University Press.
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), 943. https://doi.org/10.1126/science.aac4716
Page, S. E. (2018). The model thinker: What you need to know to make data work for you. Basic Books.
Pan, J. (2020). Welfare for autocrats: How social assistance in China cares for its rulers. Oxford University Press. https://doi.org/10.1093/oso/9780190087425.001.0001
Pariser, E. (2011). The filter bubble: What the internet is hiding from you. The Penguin Press.
Parker, G. G., Alstyne, M. W. V., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy and how to make them work for you. W. W. Norton & Company.
Parmar, N. J., Vaswani, A., Uszkoreit, J., Kaiser, L., Shazeer, N., Ku, A., & Tran, D. (2018). Image transformer. In J. Dy & A. Krause (Eds.), Proceedings of the 35th international conference on machine learning (pp. 4055–4064). PMLR. http://proceedings.mlr.press/v80/parmar18a/parmar18a.pdf
Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.
Pearl, J. (2009). Causality: Models, reasoning and inference (2nd ed.). Cambridge University Press.
Pearl, J. (2019). The seven tools of causal inference, with reflections on machine learning. Communications of the ACM, 62(3), 54–60. https://doi.org/10.1145/3241036
Pearlman, N. G. (2012). Margin of victory: How technologists help politicians win elections (N. G. Pearlman, Ed.). Praeger.
Pentland, A. (2008). Honest signals: How they shape our world. The MIT Press.
Perry, C., & DeDeo, S. (2021). The cognitive science of extremist ideologies online. arXiv. https://doi.org/10.48550/arXiv.2110.00626
Phillips, A. (2021). Unconditional equals. Princeton University Press.
Phillips, W. (2015). This is why we can’t have nice things: Mapping the relationship between online trolling and mainstream culture. The MIT Press.
Phillips, W. (2018). The oxygen of amplification: Better practices for reporting on extremists, antagonists, and manipulators online. Data & Society.
Phillips, W., & Milner, R. M. (2017). The ambivalent internet: Mischief, oddity, and antagonism online. Polity Press.
Pickard, V. (2020). Democracy without journalism? Confronting the misinformation society. Oxford University Press. https://doi.org/10.1093/oso/9780190946753.001.0001
Piper, A. (2018). Enumerations: Data and literary study. The University of Chicago Press.
Pollitt, C., & Bouckaert, G. (2017). Public management reform: A comparative analysis - into the age of austerity (4th ed.). Oxford University Press.
Popkin, S. L. (1991). The reasoning voter: Communication and persuasion in presidential campaigns. The University of Chicago Press.
Popkin, S. L. (2021). Crackup: The Republican implosion and the future of presidential politics. Oxford University Press. https://doi.org/10.1093/oso/9780190913823.001.0001
Porter, T. M. (2020). Trust in numbers: The pursuit of objectivity in science and public life (2nd ed.). Princeton University Press. (Original work published 1995)
Posegga, O. (2023). Unlocking big data: At the crossroads of computer science and the social sciences. In J. Skopek (Ed.), Research handbook digital sociology (pp. 115–129). Edward Elgar. https://doi.org/10.4337/9781789906769.00013
Posegga, O., & Jungherr, A. (2019). Characterizing political talk on Twitter: A comparison between public agenda, media agendas, and the Twitter agenda with regard to topics and dynamics. In HICSS 2019: Proceedings of the 52nd Hawaii international conference on system science (pp. 2590–2599). Scholarspace. https://doi.org/10.24251/HICSS.2019.312
Price, W. N., & Cohen, I. G. (2019). Privacy in the age of medical big data. Nature Medicine, 25, 37–43. https://doi.org/10.1038/s41591-018-0272-7
Prince, S. J. D. (2023). Understanding deep learning. The MIT Press.
Prior, M. (2007). Post-broadcast democracy: How media choice increases inequality in political involvement and polarizes elections. Cambridge University Press. https://doi.org/10.1017/CBO9781139878425
Prior, M. (2009). The immensely inflated news audience: Assessing bias in self-reported news exposure. Public Opinion Quarterly, 73(1), 130–143. https://doi.org/10.1093/poq/nfp002
Prior, M. (2017). Conditions for political accountability in a high-choice media environment. In K. Kenski & K. H. Jamieson (Eds.), The Oxford handbook of political communication (pp. 897–912). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199793471.013.63
Prior, M. (2018). Hooked: How politics captures people’s interest. Cambridge University Press.
Przeworski, A. (1991). Democracy and the market: Political and economic reforms in Eastern Europe and Latin America. Cambridge University Press. https://doi.org/10.1017/CBO9781139172493
Przeworski, A. (2018). Why bother with elections? Polity Press.
Quiring, O. (2016). Interactivity. In Quiring, o. (2016). Interactivity. The international encyclopedia of communication theory and philosophy, 1–12. (pp. 1–12). John Wiley & Sons. https://doi.org/10.1002/9781118766804.wbiect075
Rahman, H. A. (2021). The invisible cage: Workers’ reactivity to opaque algorithmic evaluations. Administrative Science Quarterly, 66(4), 945–988. https://doi.org/10.1177/00018392211010118
Rainie, L., & Wellman, B. (2012). Networked: The new social operating system. The MIT Press.
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., & Chen, M. (2022). Hierarchical text-conditional image generation with CLIP latents. arXiv. https://doi.org/10.48550/arXiv.2204.06125
Rau, J. P., & Stier, S. (2019). Die Echokammer-Hypothese: Fragmentierung der Öffentlichkeit und politische Polarisierung durch digitale Medien? Zeitschrift für Vergleichende Politikwissenschaft, 13(3), 339–417. https://doi.org/10.1007/s12286-019-00429-1
Rauchfleisch, A. (2017). The public sphere as an essentially contested concept: A co-citation analysis of the last 20 years of public sphere research. Communication and the Public, 2(1), 3–18. https://doi.org/10.1177/2057047317691054
Rauchfleisch, A., & Kaiser, J. (2020). The German far-right on YouTube: An analysis of user overlap and user comments. Journal of Broadcasting & Electronic Media, 64(3), 373–396. https://doi.org/10.1080/08838151.2020.1799690
Rauchfleisch, A., & Kaiser, J. (2021). Deplatforming the far-right: An analysis of YouTube and BitChute. Social Science Research Network. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3867818
Rauchfleisch, A., & Kovic, M. (2016). The internet and generalized functions of the public sphere: Transformative potentials from a comparative perspective. Social Media + Society, 2(2), 1–15. https://doi.org/10.1177/2056305116646393
Rauchfleisch, A., Siegen, D., & Vogler, D. (2023). How COVID-19 displaced climate change: Mediated climate change activism and issue attention in the Swiss media and online sphere. Environmental Communication, 17(3), 313–321. https://doi.org/10.1080/17524032.2021.1990978
Rauh, C., & Schwalbach, J. (2020). The ParlSpeech V2 data set: Full-text corpora of 6.3 million parliamentary speeches in the key legislative chambers of nine representative democracies. Harvard Dataverse. https://doi.org/10.7910/DVN/L4OAKN
Raymond, E. S. (1999). The cathedral and the bazaar: Musings on Linux and open source by an accidental revolutionary. O’Reilly Media.
Rheingold, H. (1993). The virtual community: Homesteading on the electronic frontier. Addison-Wesley.
Rid, T. (2020). Active measures: The secret history of disinformation and political warfare. Farrat, Straus; Giroux.
Risse, M. (2023). Political theory of the digital age: Where artificial intelligence might take us. Cambridge University Press. https://doi.org/10.1017/9781009255189
Rivero, G. (2019). Preaching to the choir: Ideology and following behaviour in social media. Contemporary Social Science, 14(1), 54–70. https://doi.org/10.1080/21582041.2017.1325924
Roberts, M. E. (2018). Censored: Distraction and diversion inside China’s great firewall. Princeton University Press.
Rochet, J.-C., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990–1029. https://doi.org/10.1162/154247603322493212
Rochet, J., & Tirole, J. (2006). Two‐sided markets: A progress report. The RAND Journal of Economics, 37(3), 645–667. https://doi.org/10.1111/j.1756-2171.2006.tb00036.x
Rosen, J. (2006). The people formerly known as the audience. PRESSthink: Ghost of Democracy in the Media Machince. http://archive.pressthink.org/2006/06/27/ppl_frmr.html
Roughgarden, T. (2016). Twenty lectures on algorithmic game theory. Cambridge University Press. https://doi.org/10.1017/CBO9781316779309
Rusbridger, A. (2018). Breaking news: The remaking of journalism and why it matters now. Canongate.
Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson Education. (Original work published 1995)
Salganik, M. J. (2018). Bit by bit: Social research in the digital age. Princeton University Press.
Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006). Experimental study of inequality and unpredictability in an artificial cultural market. Science, 311(5762), 854–856. https://doi.org/10.1126/science.1121066
Salganik, M. J., & Watts, D. J. (2009). Web-based experiments for the study of collective social dynamics in cultural markets. Topics in Cognitive Science, 1(3), 439–468. https://doi.org/10.1111/j.1756-8765.2009.01030.x
Sanders, N. E., & Schneier, B. (2021). Machine learning featurizations for AI hacking of political systems. arXiv. https://doi.org/10.48550/arXiv.2110.09231
Schäfer, A., & Zürn, M. (2021). Die demokratische Regression. Suhrkamp.
Schäfer, M. S., & Wessler, H. (2020). Öffentliche Kommunikation in Zeiten künstlicher Intelligenz. Publizistik, 65, 307–331. https://doi.org/10.1007/s11616-020-00592-6
Scharkow, M., Mangold, F., Stier, S., & Breuer, J. (2020). How social network sites and other online intermediaries increase exposure to news. PNAS: Proceedings of the National Academy of Sciences of the United States of America, 117(6), 2761–2763. https://doi.org/10.1073/pnas.1918279117
Schlozman, K. L., Brady, H. E., & Verba, S. (2018). Unequal and unrepresented: Political inequality and the people’s voice in the new gilded age. Princeton University Press.
Schmøkel, R., & Bossetta, M. (2022). FBAdLibrarian and Pykognition: Open science tools for the collection and emotion detection of images in Facebook political ads with computer vision. Journal of Information Technology & Politics, 19(1), 118–128. https://doi.org/10.1080/19331681.2021.1928579
Schneider, G. (2018). Automating drug discovery. Nature Reviews Drug Discovery, 17(97–113). https://doi.org/10.1038/nrd.2017.232
Schölkopf, B., Locatello, F., Bauer, S., Ke, N. R., Kalchbrenner, N., Goyal, A., & Bengio, Y. (2021). Toward causal representation learning. Proceedings of IEEE, 109(5), 612–634. https://doi.org/10.1109/JPROC.2021.3058954
Schroeder, R. (2014). Big Data and the brave new world of social media research. Big Data & Society, 1(2), 1–11. https://doi.org/10.1177/2053951714563194
Schroeder, R. (2018). Social theory after the internet: Media, technology and globalization. UCL Press.
Schroeder, R. (2019). Digital media and the entrenchment of right-wing populist agendas. Social Media + Society, 5(4), 1–11. https://doi.org/10.1177/2056305119885328
Schroeder, R. (2021). Digital media and the globalizing spread of populism. In D. Y. Jin (Ed.), The routledge handbook of digital media and globalization (pp. 179–187). Routledge.
Schwalbach, J., & Rauh, C. (2021). Collecting large-scale comparative text data on legislative debate. In H. Back, M. Debus, & J. M. Fernandes (Eds.), The politics of legislative debate (pp. 91–109). Oxford University Press. https://doi.org/10.1093/oso/9780198849063.001.0001
Schwartzberg, M. (2015). Epistemic democracy and its challenges. Annual Review of Political Science, 18, 187–203. https://doi.org/10.1146/annurev-polisci-110113-121908
Schwartzel, E. (2022). Red carpet: Hollywood, china, and the global battle for cultutal supremacy. Penguin Press.
Schwemmer, C., Unger, S., & Heiberger, R. (2023). Automated image analysis for studying online behaviour. In J. Skopek (Ed.), Research handbook of digital sociology (pp. 278–291). Edward Elgar. https://doi.org/10.4337/9781789906769.00023
Scott, J. C. (1998). Seeing like a state: How certain schemes to improve the human condition have failed. Yale University Press.
Scott, J. C. (2009). The art of not being governed: An anarchist history of upland southeast asia. Yale University Press.
Scott, M., Bunce, M., & Wright, K. (2019). Foundation funding and the boundaries of journalism. Journalism Studies, 20(14), 2034–2052. https://doi.org/10.1080/1461670X.2018.1556321
Segal, A. (2021). Huawei, 5G, and weaponized interdependence. In D. W. Drezner, H. Farrell, & A. L. Newman (Eds.), The uses and abuses of weaponized interdependence (pp. 149–168). Brookings Institution Press.
Settle, J. E. (2018). Frenemies: How social media polarizes America. Cambridge University Press. https://doi.org/10.1017/9781108560573
Shapiro, C., & Varian, H. R. (1999). Information rules: A strategic guide to the network economy. Harvard Business Review Press.
Shifman, L. (2016). Cross-cultural comparisons of user-generated content: An analytical framework. International Journal of Communication, 10, 5644–5663.
Shirky, C. (2008). Here comes everybody: The power of organizing without organizations. The Penguin Press.
Shoemaker, P. J., & Reese, S. D. (2014). Mediating the message in the 21st century (3rd ed.). Routledge.
Shoemaker, P. J., & Vos, T. P. (2009). Gatekeeping theory. Routledge.
Sides, J., & Vavreck, L. (2014). Obama’s not-so-big data. Pacific Standard. http://www.psmag.com/navigation/politics-and-law/obamas-big-data-inconclusive-results-political-campaigns-72687/
Sifry, M. L. (2023). Can democrats be ’people-first’ if their campaigns value people last? The Connector. https://theconnector.substack.com/p/can-democrats-be-people-first-if
Silge, J., & Robinson, D. (2017). Text mining with r: A tidy approach. O’Reilly Media.
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., Dieleman, S., Grewe, D., Nham, J., Kalchbrenner, N., Sutskever, I., Lillicrap, T., Leach, M., Kavukcuoglu, K., Graepel, T., & Hassabis, D. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529, 484–489. https://doi.org/10.1038/nature16961
Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., Lillicrap, T., Simonyan, K., & Hassabis, D. (2018). A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science, 362(6419), 1140–1144. https://doi.org/10.1126/science.aar6404
Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A., Chen, Y., Lillicrap, T., Hui, F., Sifre, L., van den Driessche, G., Graepel, T., & Hassabis, D. (2017). Mastering the game of Go without human knowledge. Nature, 550, 354–359. https://doi.org/10.1038/nature24270
Simitis, S. (1987). Reviewing privacy in an information society. University of Pennsylvania Law Review, 135(3), 707–746. https://doi.org/10.2307/3312079
Simitis, S. (1995). From the market to the polis: The EU directive on the protection of personal data. Iowa Law Review, 80(3), 445–469.
Simon, F. M., Altay, S., & Mercier, H. (2023). Misinformation reloaded? Fears about the impact of generative AI on misinformation are overblown. Harvard Kennedy School Misinformation Review, 4(5), 1–11. https://doi.org/10.37016/mr-2020-127
Singh, S. (2020). Special delivery: How internet platforms use artificial intelligence to target and deliver ads. New America Foundation. https://www.newamerica.org/oti/reports/special-delivery/
Sı́thigh, D. M., & Siems, M. (2019). The Chinese Social Credit System: A model for other countries? Morden Law Review, 82(6), 1034–1071. https://doi.org/10.1111/1468-2230.12462
Smith, B. C. (2019). The promise of artificial intelligence: Reckoning and judgment. The MIT Press.
Solove, D. J. (2008). Understanding privacy. Harvard University Press.
Somashekhar, S. P., Sepúlveda, M.-J., Puglielli, S., Norden, A. D., Shortliffe, E. H., Kumar, C. R., Rauthan, A., Kumar, N. A., Patil, P., Rhee, K., & Ramya, Y. (2018). Watson for oncology and breast cancer treatment recommendations: Agreement with an expert multidisciplinary tumor board. Annals of Oncology, 29(2), 418–423. https://doi.org/10.1093/annonc/mdx781
Soni, J. (2022). The founders: The story of paypal and the entrepreneurs who shaped silicon valley. Simon & Schuster.
Sprietsma, M. (2013). Discrimination in grading: Experimental evidence from primary school teachers. Empirical Economics, 45(1), 523–538. https://doi.org/10.1007/s00181-012-0609-x
Spufford, F. (2010). Red plenty: Inside the Fifties’ Soviet dream. Faber & Faber.
Stier, S., Breuer, J., Siegers, P., & Thorson, K. (2020). Integrating survey data and digital trace data: Key issues in developing an emerging field. Social Science Computer Review, 38(5), 503–516. https://doi.org/10.1177/0894439319843669
Stier, S., Mangold, F., Scharkow, M., & Breuer, J. (2022). Post post-broadcast democracy? News exposure in the age of online intermediaries. American Political Science Review, 116(2), 768–774. https://doi.org/10.1017/S0003055421001222
Stier, S., Posch, L., Bleier, A., & Strohmaier, M. (2017). When populists become popular: Comparing Facebook use by the right-wing movement Pegida and German political parties. Information, Communication & Society, 20(9), 1365–1388. https://doi.org/10.1080/1369118X.2017.1328519
Stone, B. (2013). The everything store: Jeff bezos and the age of amazon. Little, Brown; Company.
Stone, B. (2017). The upstarts: How Uber, Airbnb, and the killer companies of the new Silicon Valley are changing the world. Black Bay Books.
Stone, B. (2021). Amazon unbound: Jeff bezos and the invention of a global empire. Simon & Schuster.
Stopczynski, A., Sekara, V., Sapiezynski, P., Cuttone, A., Madsen, M. M., Larsen, J. E., & Lehmann, S. (2014). Measuring large-scale social networks with high resolution. PLoS One, 9(4), e95978. https://doi.org/10.1371/journal.pone.0095978
Stromer-Galley, J. (2000). On-line interaction and why candidates avoid it. Journal of Communication, 50(4), 111–132. https://doi.org/10.1111/j.1460-2466.2000.tb02865.x
Stromer-Galley, J. (2019). Presidential campaigning in the internet age (2nd ed.). Oxford University Press. https://doi.org/10.1093/oso/9780190694043.001.0001 (Original work published 2014)
Strossen, N. (2018). Hate: Why we should resist it with free speech, not censorship. Oxford University Press.
Subhayan Mukerjee, S. G.-B., Sı́lvia Majó-Vázquez. (2018). Networks of audience overlap in the consumption of digital news. Journal of Communication, 68(1), 26–50. https://doi.org/10.1093/joc/jqx007
Sunstein, C. R. (2001). Republic.com. Princeton University Press.
Tai, Y., & Fu, K. (2020). Specificity, conflict, and focal point: A systematic investigation into social media censorship in China. Journal of Communication, 70(6), 842–867. https://doi.org/10.1093/joc/jqaa032
Tausczik, Y. R., & Pennebaker, J. W. (2010). The psychological meaning ofWords: LIWC and computerized text analysis methods. Journal of Language and Social Psychology, 29(1), 24–54. https://doi.org/10.1177/0261927X09351676
Taylor, C. (1993). Modernity and the rise of the public sphere. In G. B. Peterson (Ed.), The tanner lectures on human values (pp. 203–260). University of Utah Press. https://tannerlectures.utah.edu/_resources/documents/a-to-z/t/Taylor93.pdf
Taylor, C. (1995). Liberal politics and the public sphere. In Philosophical arguments (pp. 257–288). Harvard University Press.
Taylor, F. W. (1911). The principles of scientific management. Harper & Brothers.
Teo, E., & Fu, K. (2021). A novel systematic approach of constructing protests repertoires from social media: Comparing the roles of organizational and non-organizational actors in social movement. Journal of Computational Social Science Volume, 4(2), 787–812. https://doi.org/10.1007/s42001-021-00101-3
Tetlock, P. E. (2017). Expert political judgment: How good is it? How can we know? (Revised). Princeton University Press. (Original work published 2005)
Thelen, K. (2018). Regulating Uber: The politics of the platform economy in Europe and the United States. Perspectives on Politics, 16(4), 938–953. https://doi.org/10.1017/S1537592718001081
Theocharis, Y., & Jungherr, A. (2021). Computational social science and the study of political communication. Political Communication, 38(1–2), 1–22. https://doi.org/10.1080/10584609.2020.1833121
Theocharis, Y., Lowe, W., van Deth, J. W., & Garcı́a-Albacete, G. (2015). Using twitter to mobilize protest action: Online mobilization patterns and action repertoires in the Occupy Wall Street, Indignados, and Aganaktismenoi movements. Information, Communication & Society, 18(2), 202–220. https://doi.org/10.1080/1369118X.2014.948035
Theocharis, Y., Vitoratou, S., & Sajuria, J. (2017). Civil society in times of crisis: Understanding collective action dynamics in digitally-enabled volunteer networks. Journal of Computer-Mediated Communication, 22(5), 248–265. https://doi.org/10.1111/jcc4.12194
Thompson, C. (2019). Coders: The making of a new tribe and the remaking of the world. Penguin Press.
Tiffany, K. (2022). Everything i need i get from you: How fangirls created the internet as we know it. Farrat, Straus; Giroux.
Tilly, C. (2007). Democracy. Cambridge University Press. https://doi.org/10.1017/CBO9780511804922
Timberg, C., & Gardner, A. (2012). Democrats push to redeploy Obama’s voter database. The Washington Post. https://www.washingtonpost.com/business/economy/democrats-push-to-redeploy-obamas-voter-database/2012/11/20/d14793a4-2e83-11e2-89d4-040c9330702a_story.html
Toepfl, F., & Piwoni, E. (2015). Public spheres in interaction: Comment sections of news websites as counterpublic spaces. Journal of Communication, 65(3), 465–488. https://doi.org/10.1111/jcom.12156
Trask, A. W. (2019). Grokking deep learning. Manning Publications Co.
Trippi, J. (2004). The revolution will not be televised: Democracy, the internet, and the overthrow of everything. Regan Books.
Tse, E. (2015). China’s disruptors: How alibaba, xiaomi, tencent and other companies are changing the rules of business. Portfolio/Penguin.
Tucker, J. A., Theocharis, Y., Roberts, M. E., & Barberá, P. (2017). From liberation to turmoil: Social media and democracy. Journal of Democracy, 28(4), 46–59.
Tufekci, Z. (2017). Twitter and tear gas: The power and fragility of networked protest. Yale University Press.
Turner, F. (2006). From counterculture to cyberculture: Stewart brand, the whole earth network, and the rise of digital utopianism. The University of Chicago Press.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1134. https://doi.org/10.1126/science.185.4157.1124
Underwood, T. (2019). Distant horizons: Digital evidence and literary change. The University of Chicago Press.
Usher, N. (2021). News for the rich, white, and blue: How place and power distort American journalism. Columbia University Press.
Van Bavel, J. J., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M., Crockett, M. J., Crum, A. J., Douglas, K. M., Druckman, J. N., Drury, J., Dube, O., Ellemers, N., Finkel, E. J., Fowler, J. H., Gelfand, M., Han, S., Haslam, S. A., Jetten, J., … Wille, R. (2020). Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behavior, 4, 460–471. https://doi.org/10.1038/s41562-020-0884-z
van der Vlist, F., Helmond, A., Burkhardt, M., & Seitz, T. (2022). API governance: The case of Facebook’s evolution. Social Media + Society, 8(2), 1–24. https://doi.org/10.1177/20563051221086228
van Dijck, J., Poell, T., & Waal, M. de. (2018). The platform society: Public values in a connective world. Oxford University Press. https://doi.org/10.1093/oso/9780190889760.001.0001
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention is all you need. In I. Guyon, U. von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. V. N. Vishwanathan, & R. Garnett (Eds.), NIPS 2017: 31st conference on neural information processing systems (Vol. 30, pp. 1–11). Curran Associates, Inc. https://proceedings.neurips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf
Vela, D., Sharp, A., Zhang, R., Nguyen, T., & Oleg S. Pianykh, A. H. an. (2022). Temporal quality degradation in AI models. Scientific Reports, 12(11654), 1–12. https://doi.org/10.1038/s41598-022-15245-z
Wallace, J. L. (2022). Seeking truth & hiding facts: Information, ideology, & authoritarianism in china. Oxford University Press. https://doi.org/10.1093/oso/9780197627655.001.0001
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge University Press. https://doi.org/10.1017/CBO9780511815478
Watts, D. J. (2011). Everything is obvious: How common sense fails us. Random House.
Weber, V. (2019). Understanding the global ramifications of china’s information-control model. In N. D. Wright (Ed.), Artificial intelligence, china, russia, and the global order: Technological, political, global, and creative perspectives (pp. 76–80). Air University Press.
Weidmann, N. B. (2023). Data management for social scientists: From files to datasets. Cambridge University Press. https://doi.org/10.1017/9781108990424
Wells, C., Pevehouse, D. V. S. J. C., Yang, J., Pelled, A., Boehm, F., Lukito, J., Ghosh, S., & Schmidt, J. L. (2016). How Trump drove coverage to the nomination: Hybrid media campaigning. Political Communication, 33(4), 669–676. https://doi.org/10.1080/10584609.2016.1224416
Wessler, H. (2018). Habermas and the media. Polity Press.
Westin, A. F. (1967). Privacy and freedom. Atheneum.
Wiedeman, R. (2020). Times change. New York Magazine. https://nymag.com/intelligencer/2020/11/inside-the-new-york-times-heated-reckoning-with-itself.html
Wilkinson, A. (2023). The looming threat of AI to Hollywood, and why it should matter to you. Vox. https://www.vox.com/culture/23700519/writers-strike-ai-2023-wga
Williams, B. A., & Carpini, M. X. D. (2011). After broadcast news: Media regimes, democracy, and the new information environment. Cambridge University Press. https://doi.org/10.1017/CBO9780511846366
Williams, N. W., Casas, A., & Wilkerson, J. D. (2020). Images as data for social science research. Cambridge University Press. https://doi.org/10.1017/9781108860741
Windsor, L. C. (2021). Advancing interdisciplinary work in computational communication science. Political Communication, 38(1–2), 182–191. https://doi.org/10.1080/10584609.2020.1765915
Wintrobe, R. (1998). The political economy of dictatorship. Cambridge University Press. https://doi.org/10.1017/CBO9781139174916
Wolfram, S. (2023). What is ChatGPT doing and why does it work? Wolfram Media, Inc.
Wooldridge, A. (2011). Masters of management: How the business gurus and their ideas have changed the world—for better and for worse. Harper Collins.
Woolridge, M. (2020). The road to conscious machines: The story of AI. Pelican Books.
Wright, J., & Ma, Y. (2022). High-dimensional data analysis with low-dimensional models: Principles, computation, and applications. Cambridge University Press. https://doi.org/10.1017/9781108779302
Wright, K., Scott, M., & Bunce, M. (2019). Foundation-funded journalism, philanthrocapitalism and tainted donors. Journalism Studies, 20(5), 675–695. https://doi.org/10.1080/1461670X.2017.1417053
Wuttke, A. (2019). Why too many political science findings cannot be trusted and what we can do about it: A review of meta-scientific research and a call for academic reform. Politische Vierteljahresschrift, 60(1), 1–19. https://doi.org/10.1007/s11615-018-0131-7
Yang, E., & Roberts, M. E. (2023). The authoritarian data problem. Journal of Democracy, 34(4), 141–150. https://doi.org/10.1353/jod.2023.a907695
Yang, T., Majó-Vásquez, S., Nielsen, R. K., & González-Bailón, S. (2020). Exposure to news grows less fragmented with an increase in mobile access. PNAS: Proceedings of the National Academy of Sciences of the United States of America, 117(46), 28678–28683. https://doi.org/10.1073/pnas.2006089117
Young, I. M. (2002). Inclusion and democracy. Oxford University Press. https://doi.org/10.1093/0198297556.001.0001
Zaller, J. R. (1992). The nature and origins of mass opinion. Cambridge University Press. https://doi.org/10.1017/CBO9780511818691
Zammito, J. H. (2012). The second life of the “public sphere”: On charisma and routinization in the history of a concept. In C. J. Emden & D. Midgley (Eds.), Changing perceptions of the public sphere (pp. 90–119). Berghahn Books.
Zhang, Y., Shah, D., Foley, J., Abhishek, A., Lukito, J., Suk, J., Kim, S. J., Sun, Z., Pevehouse, J., & Garlough, C. (2019). Whose lives matter? Mass shootings and social media discourses of sympathy and policy, 2012–2014. Journal of Computer-Mediated Communication, 24(4), 182–202. https://doi.org/10.1093/jcmc/zmz009
Zhu, Y. (2022). Hollywood in china: Behind the scenes of the world’s largest movie market. The New Press.
Ziegele, M., Breiner, T., & Quiring, O. (2014). What creates interactivity in online news discussions? An exploratory analysis of discussion factors in user comments on news items. Journal of Communication, 64(6), 1111–1138. https://doi.org/10.1111/jcom.12123
Zuckerberg, M. (2017). I believe the most important thing we can do is work to bring people closer together. Facebook. https://www.facebook.com/notes/393134628500376/
Zwolinski, M., & Tomasi, J. (2023). The individualists: Radicals, reactionaries, and the struggle for the soul of libertarianism. Princeton University Press.