Please sign up for your presentation time slot here.

Presentation timetable

For fairness, the order of presentations will be generated with random sampling for groups (subject to the conditions for when students said they would be unable to present).

W10 - March 5 Emil Mønster & Lau Madsen
W11 - March 12 Marie Dam Christoffersen and Amalie Skourup Juul Jensen
W11 - March 12 Elias Paludan
W12 - March 19 Nikolai Mizani
W13 - March 26 —
W14 - April 2 André Nabeu, Max Pontoppidan, Nikolaj Nielsen-Friis
W15 - April 9 Luna Asta Dalsgaard Wenning & Maria Røpke Midjord
W15 - April 9 Giovanni Astante
W16 - April 16 Frederik Bast
W16 - April 16 Karin Kaasgaard, Emma Kraft, Signe Sørensen
W17 - April 23 Mathias Andersen
W17 - April 23 Hifsa & Katrine
W18 - April 30 Thea Thysgaard
W19 - May 7 Lennart Zinck
W19 - May 7 Victor Schousboe
W20 - May 14 August Taankvist & Sebastian Holst

Instructions for audience members

Before each class in which we will have presentations, please “read” the articles being presented. By “read”, I mean the following:

  1. Skim the abstract
  2. Skim the introduction
  3. Skim the theory/hypotheses
  4. Read the research design to a sufficient extent that you have a good understanding of the data and methods involved
  5. Read the results section in more depth
  6. Skim the conclusion

Keeping up with research means being able to read strategically. By “skim”, I also mean skipping whole paragraphs, or trying to pick out sentences that get to the heart of, say, the theory, or research design.

Prepare a question to ask the presenters:

  1. A critical question about the paper
  2. A criticism of the paper (for the presenter(s) to respond to)

Instructions for presenters

For your presentation, you are expected to take the role of the author(s) of the paper that you are presenting. Because this course is designed to emphasize research design and analysis, you should know the details of the research design, empirical results, and robustness checks extremely well. You should also have a broad understanding of the literature that the results and theory speak to.

Basic details

  1. Present an empirically driven academic article that uses social media data (see examples below)
  2. The presentation should be roughly 6-7 minutes long
    • time and practice your presentation before you give it to the class
  3. Have slides, and present relevant tables and figures
  4. Have an appendix to your slides (as appropriate)
    • these might include additional results, figures, or robustness checks

Presentation structure

  1. Motivation for the research
    • Very short
  2. Research question(s) or goal(s)
    • Very short
  3. Theory, and its link to the empirical expectations (i.e. the hypotheses)
    • Very short
  4. Research design, data, and methods
  5. Results (including tables & figures)
    • Present only what you consider the main findings
    • i.e. If a finding is essential to the story of the article, then present it
  6. Caveats about the results or design + your own thoughts on the quality of the research and design

The emphasis placed on each of these 6 points will differ strongly between articles. Papers in computer science, for example, frequently have very little theory. Other papers are primarily descriptive, without formal (or informal) hypotheses. So please feel free to use the above structure as a guide.

Note: If you are in a group, only one person can present (if you prefer). For example, if you are in a group of 3 and you think it best for only 1 person to present, that’s perfectly alright. During the question and answer section, any members of a group can then provide answers. I expect, of course, that you fairly divide up tasks for developing and giving the presentation.

Example presentation

Example presentation slides

Potential articles to present

Below are a number of articles concerning social media and politics. You are welcome to present any of them, or one that you find on your own. If you do not see an article that covers the topic that you are interested in, please feel free to ask me if I have any recommendations for other articles.

  1. How Censorship in China Allows Government Criticism but Silences Collective Expression
    American Political Science Review, 2013, 107 (2): 326-343
    Gary King, Jennifer Pan, and Margaret E. Roberts

  2. Reverse-engineering Censorship in China: Randomized Experimentation and Participant Observation
    Science, 2014, 345 (6199): 1-10
    Gary King, Jennifer Pan, and Margaret E. Roberts
    • Gary King discusses the results in a podcast here

  3. How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument
    American Political Science Review, 2017, 111 (3): 484-501
    Gary King, Jennifer Pan, and Margaret E. Roberts
    • New York Times article about the study here

  4. Concealing Corruption: How Chinese Officials Distort Upward Reporting of Online Grievances
    American Political Science Review, 2018, 112 (3): 602-620
    Jennifer Pan and Kaiping Chen

  5. How Sudden Censorship Can Increase Access to Information
    American Political Science Review, 2018, 112 (3): 484-501
    William R. Hobbs and Margaret E. Roberts

  6. The Impact of Media Censorship: 1984 or Brave New World?
    American Economic Review, 2019, 109 (6): 2294-2332
    Yuyu Chen and David Y. Yang

  7. Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest
    Political Science Research and Methods, 2019, 7 (4): 815-834
    Kevin Munger, Richard Bonneau, Jonathan Nagler, and Joshua A. Tucker

  8. #No2Sectarianism: Experimental Approaches to Reducing Sectarian Hate Speech Online
    American Political Science Review, 2021, 114 (3): 837-855
    Alexandra Siegel and Vivienne Badaan

  9. Social Networks and Protest Participation
    American Journal of Political, 2019, 63 (3): 690-705.
    Jennifer M. Larson, Jonathan Nagler, Jonathan Ronen, and Joshua A. Tucker

  10. From Isolation to Radicalization: Anti-Muslim Hostility and Support for ISIS in the West
    American Political Science Review, 2019, 113 (1): 173-194
    Tamar Mitts

  11. Effects of Divisive Political Campaigns on the Day-to-Day Segregation of Arab and Muslim Americans
    American Political Science Review, 2019, 113 (1): 270-276
    William Hobbs and Nazita Lajevardi

  12. Fanning the Flames of Hate: Social Media and Hate Crime
    Journal of the European Economic Association, Forthcoming: 1-37.
    Karsten Müller and Carlo Schwarz
    + Coverage in the New York Times here
    + Criticism of the paper by Tyler Cowen here

  13. You Can’t Stay Here: The Efficacy of Reddit’s 2015 Ban Examined Through Hate Speech
    Proceedings of the ACM on Human-Computer Interaction, 2017, 1 (2): 1-22
    Eshwar Chandrasekharan, Umashanthi Pavalanathan, Anirudh Srinivasan, Adam Glynn, Jacob Eisenstein, and Eric Gilbert

  14. Politicians in the Line of Fire: Incivility and the Treatment of Women on Social Media
    Research & Politics, 2019, January-March: 1-7
    Ludovic Rheault, Erica Rayment, and Andreea Musulan

  15. Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment
    Political Behavior, 2017, 39 (3): 629-649
    Kevin Munger

  16. Can Exposure to Celebrities Reduce Prejudice? The Effect of Mohamed Salah on Islamophobic Behaviors and Attitudes
    Working Paper No. 19-04, Immigration Policy Lab, May
    Ala’ Alrababa’h, William Marble, Salma Mousa, and Alexandra Siegel
    • Coverage of the article in The Economist here

  17. Preventing Harassment and Increasing Group Participation through Social Norms in 2,190 Online Science Discussions
    Proceedings of the National Academy of Sciences, 2019, 116 (20): 9785-9789
    J. Nathan Matias

  18. Filter Bubbles, Echo Chambers, and Online News Consumption
    Public Opinion Quarterly, 2016, 80 (S1): 298-320
    Seth Flaxman, Sharad Goel, and Justin M. Rao

  19. 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, 2018, 115 (37): 9216-9221
    Christopher Bail, Lisa Argyle, Taylor Brown, John Bumpus, Haohan Chen, M. B. Fallin Hunzaker, Jaemin Lee, Marcus Mann, Friedolin Merhout, and Alexander Volfovsky
    • New York Times article about the study here

  20. Fake News on Twitter during the 2016 U.S. Presidential Election
    Science, 2019, 363: 374–378
    Nir Grinberg, Kenneth Joseph, Lisa Friedland, Briony Swire-Thompson, and David Lazer

  21. The Spread of True and False News Online
    Science, 2018, 359 (6380): 1146-1151
    Soroush Vosoughi, Deb Roy, and Sinan Aral

  22. Less Than You Think: Prevalence and Predictors of Fake News Dissemination on Facebook
    Science Advances, 2019, 5 (1): 1-8
    Andrew Guess, Jonathan Nagler, and Joshua Tucker

  23. A 61-million-person Experiment in Social Influence and Political Mobilization
    Nature, 2012, 489: 295-298
    Robert M. Bond, Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle, and James H. Fowler

  24. The Welfare Effects of Social Media
    American Economic Review, 2020, 110 (3): 629-676
    Hunt Allcott, Luca Braghieri, Sarah Eichmeyer, and Matthew Gentzkow

  25. Experimental Evidence of Massive-scale Emotional Contagion through Social Networks
    Proceedings of the National Academy of Sciences, 2014, 111 (24): 8788-8790
    Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. Hancock

  26. Who Leads? Who Follows? Measuring Issue Attention and Agenda Setting by Legislators and the Mass Public Using Social Media Data
    American Political Science Review, 2019, 113 (4): 883-901
    Pablo Barberá, Andreu Casas, Jonathan Nagler, Patrick J. Egan, Richard Bonneau, John T. Jost, and Joshua A. Tucker

  27. Political Advertising Online and Offline
    American Political Science Review, 2021, 115 (1): 130-149
    Erika Franklin Fowler, Michael M. Franz, Gregory J. Martin, Zachary Peskowitz, and Travis N. Ridout

  28. Exposure to Ideologically Diverse News and Opinion on Facebook
    Science, 2015, 348 (6239): 1130-1132
    Eytan Bakshy, Solomon Messing, and Lada A. Adamic

  29. Discrimination through Optimization: How Facebook’s Ad Delivery can Lead to Skewed Outcomes
    Proceedings of the ACM on Human-Computer Interaction, 3 (CSCW): 1-30
    Muhammad Ali, Piotr Sapiezynski, Miranda Bogen, Aleksandra Korolova, Alan Mislove, and Aaron Rieke

  30. Assessing the Russian Internet Research Agency’s Impact on the Political Attitudes and Behaviors of American Twitter Users in Late 2017
    Proceedings of the National Academy of Sciences, 2020, 117 (1): 243-250
    Christopher A. Bail, Brian Guay, Emily Maloney, Aiden Combs, D. Sunshine Hillygus, Friedolin Merhout, Deen Freelon, and Alexander Volfovsky