ASTK18251U Critical Issues in the Politics of Social Media

Volume 2019/2020
Education

Bachelor student (2012 programme curriculum): 10 ECTS

Bachelor student (2017 programme curriculum): 7.5 ECTS

Master student: 7.5 ECTS

Content

This course will provide an examination of the increasing role of social media and algorithms on information consumption, attitudes, and behaviour in political life. Given the rapidly expanding role of social media in politics, the topics examined in the course will be many and varied.

They include the extent to which there is ideological bias in our consumption and sharing of political news; the role and diffusion of misinformation and fake news online; the use of social media to overcome barriers to political protest and organization; rumors and the incitement of political and communal violence; gender bias, racism, and hate speech in social media interactions; whether social media leads to political polarization; the ability of search algorithms to determine the information that we consume; and the use of social media and censorship by governments to influence the attitudes and behavior of citizens domestically and those of international adversaries.

Given the rapid shifts in the topics and research in social media, the course will examine many of the most recent theoretical and empirical developments in social media research and, where possible, their intersection with real-world events as they occur during the course.

 

 

Learning Outcome

Knowledge: Upon completion of the course, students will (1) be able to describe the key debates and research questions in the academic literature concerning the politics of social media, and (2) be able reflect on the evidence adduced in favour of each theory of information-seeking, attitude formation, and behaviour presented in the course.

 

Skills: Students will be able to critically analyze both the quantitative and qualitative evidence relevant to each research question and theory concerning the study of politics and social media.

 

Competences: Students will be able to formulate a plan to theoretically approach and scientifically examine new and emerging research questions in the study of social media and politics.

 

Examples of material included in this course:

 

Persily, N. (2017). Can democracy survive the internet? Journal of Democracy, 28(2):63–76.

 

Tucker, J. A., Theocharis, Y., Roberts, M. E., and Barberá, P. (2017). From liberation to turmoil: Social media and democracy. Journal of Democracy, 28(4):46–59.

 

Tufekci, Z. and Wilson, C. (2012). Social media and the decision to participate in political protest: Observations from tahrir square. Journal of Communication, 62(2):363–379.

 

Bail, C., Argyle, L., Brown, T., Bumpus, J., Chen, H., Hunzaker, M. B. F., Lee, J., Mann, M., Merhout, F., and Volfovsky, A. (2018). Exposure to opposing views can increase political polarization: Evidence from a large-scale field experiment on social media. Proceedings of the National Academy of Sciences, 115(37):9216–9221.

 

Jost, J. T., Barberá, P., Bonneau, R., Langer, M., Metzger, M., Nagler, J., Sterling, J., and Tucker, J. A. (2018). How social media facilitates political protest: Information, motivation, and social networks. Advances in Political Psychology, 39(S1):85–118.

 

Mitts, T. (Forthcoming). From isolation to radicalization: Anti-muslim hostility and support for isis in the west. American Political Science Review, pages 1–22.

 

Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D. I., Marlow, C., Settle, J. E., and Fowler, J. H. (2012). A 61-million-person experiment in social influence and political mobilization. Nature, 489:295–298.

 

Settle, J. E., Bond, R. M., Coviello, L., Fariss, C. J., Fowler, J. H., and Jones, J. J. (2016). From posting to voting: The effects of political competition on online political engagement. Political Science Research and Methods, 4(2):361–378.

 

Allcott, H., Braghieri, L., Eichmeyer, S., and Gentzkow, M. (2019). The welfare effects of social media. Unpublished manuscript, January 27.

 

Boxell, L., Gentzkow, M., and Shapiro, J. M. (2017). Greater internet use is not associated with faster growth in political polarization among us demographic groups. Proceedings of the National Academy of Sciences, 114(40):10612–10617.

 

Bail, C., Argyle, L., Brown, T., Bumpus, J., Chen, H., Hunzaker, M. B. F., Lee, J., Mann, M., Merhout, F., and Volfovsky, A. (2018). Exposure to opposing views can increase political polarization: Evidence from a large-scale field experiment on social media. Proceedings of the National Academy of Sciences, 115(37):9216–9221.

 

Flaxman, S., Goel, S., and Rao, J. M. (2016). Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(S1):298–320.

 

Sivak, E. and Smirnov, I. (2019). Parents mention sons more often than daughters on social media. Proceedings of the National Academy of Sciences, 116(6):2039–2041.

 

Rheault, L., Rayment, E., and Musulan, A. (2019). Politicians in the line of fire: Incivility and the treatment of women on social media. Research & Politics, January-March:1–7.

 

Munger, K. (2017). Tweetment effects on the tweeted: Experimentally reducing racist harassment. Political Behavior, 39(3):629–649.

 

King, G., Pan, J., and Roberts, M. E. (2014). Reverse-engineering censorship in china: Randomized experimentation and participant observation. Science, 345(6199):1–10.

 

King, G., Pan, J., and Roberts, M. E. (2017). How the chinese government fabricates social media posts for strategic distraction, not engaged argument. American Political Science Review, 111(3):484–501.

 

Hobbs, W. R. and Roberts, M. E. (Forthcoming). How sudden censorship can increase access to information. American Political Science Review, pages 1–16.

 

Zeitzoff, T. (Forthcoming). Does social media influence conflict? evidence from the 2012 gaza conflict. Journal of Conflict Resolution, pages 1–35.

 

Barberá, P. and Zeitzoff, T. (2018). The new public address system: Why do world leaders adopt social media? International Studies Quarterly, 62(1):121–130.

 

Brady, W. J., Wills, J. A., Jost, J. T., Tucker, J. A., and Van Bavel, J. J. (2017). Emotion shapes the diffusion of moralized content in social networks. Proceedings of the National Academy of Sciences, 114(28):7313–7318.

 

Iyengar, S. and Massey, D. S. (Forthcoming). Scientific communication in a post-truth society. Proceedings of the National Academy of Sciences, pages 1–6.

 

Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., and Lazer, D. (2019). Fake news on twitter during the 2016 u.s. presidential election. Science, 363:374–378.

 

Pennycook, G. and Rand, D. G. (Forthcoming). Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences, pages 1–6.

 

Guess, A., Nagler, J., and Tucker, J. (2019). Less than you think: Prevalence and predictors of fake news dissemination on facebook. Science Advances, 5(1):1–8.

 

Bond, R. and Messing, S. (2015). Quantifying social media’s political space: Estimating ideology from publicly revealed preferences on facebook. American Political Science Review, 109(1):62–78.

 

Messing, S., van Kessel, P., and Hughes, A. (2017). Sharing the news in a polarized congress: Partisan and ideological divides shape which news outlets legislators share links to on facebook. Pew Research Center, December 17.

Much research concerning the politics of social media uses data, and thus relies heavily on quantitative research designs. Students should therefore be relatively comfortable understanding basic descriptions of quantitative research and statistical testing. Students will not, however, be expected to conduct such analysis themselves.
Teaching will be conducted through a combination of weekly lectures, student presentations, and class discussions.
  • Category
  • Hours
  • Class Instruction
  • 28
  • Total
  • 28
Written
Oral
Individual
Continuous feedback during the course of the semester
Peer feedback (Students give each other feedback)
Credit
7,5 ECTS
Type of assessment
Written assignment
Free assignment
Marking scale
7-point grading scale
Censorship form
No external censorship
Re-exam

Free written assignment

Criteria for exam assesment
  • Grade 12 is given for an outstanding performance: the student lives up to the course's goal description in an independent and convincing manner with no or few and minor shortcomings
  • Grade 7 is given for a good performance: the student is confidently able to live up to the goal description, albeit with several shortcomings
  • Grade 02 is given for an adequate performance: the minimum acceptable performance in which the student is only able to live up to the goal description in an insecure and incomplete manner