Applied psephology



Tom Gauld:

Voting system

On the practicalities of voter modeling in elections, for the purpose of influencing how they vote, with special reference to Australian elections. Marketing psychology for governments, and for those who wish to have control of governments. This also relates, in these increasingly polarised times, to the difficulties of getting along.

For now, a smattering of links.

πŸ— mention problems of ecological inference, Simpson’s paradoxes in electoral demographics, β€œSymbolic data analysis” for census data, response bias, survey design etc. Finish up with practical tips.

Betting on them

You mean in a prediction market? See the nice plots from David Rothschild via Andrew Gelman, and Davis’s introduction to shortcoming, and consider also Taleb’s arbitrage argument. (Taleb 2018)

Practicalities

  • Presumably spatial statistics and other resources such as Geocomputation with R relate.

  • that Wired article that made A/B testing hip way back in the day.

    I wanted to excerpt a thing from that, but they want to charge me money for even that, and as I don’t actually like Wired magazine per se, I cannot be arsed.

  • How do you do psephological graphical models? causalimpact a la (Brodersen et al. 2015)? Or is a straight-up PC-algorithm causal study sufficient? How about when the data is a mixture of time-series data and one-off results (e.g. polling before and election and the election itself) How do you integrate external information such as population mobility?

Australian specifics

See Australia in data for some technicalities of how to access data about Australia.

Kevin Bonham does a lengthy postmortem about the local polling fails such as suspiciously low variance, assertions they lack education-based poststratification. Other local experts include Adrian Beaumont.

On voters strategically changing electorates

What are the marginal benefits of treating politics like the porkbarrel machine it seems to be and behave accordingly? I’d like it to be otherwise, but let’s work with what we have.

Optimal electoral marginalness, inverse gerrymandering etc. Invading marginal electorates. Organised opposition means one would be are more likely to claim council seats as a side benefit.

How well could you do this? How static are the preferences of the voters?

References

Acemoglu, Daron, Asuman Ozdaglar, and Ali ParandehGheibi. 2010. β€œSpread of (Mis)information in Social Networks.” Games and Economic Behavior 70 (2): 194–227.
Achlioptas, Dimitris, Aaron Clauset, David Kempe, and Cristopher Moore. 2005. β€œOn the Bias of Traceroute Sampling: Or, Power-Law Degree Distributions in Regular Graphs.” In Proceedings of the Thirty-Seventh Annual ACM Symposium on Theory of Computing, 694–703. STOC ’05. New York, NY, USA: ACM.
Andrew Crooks. n.d. β€œBot Stamina: Examining the Influence and Staying Power of Bots in Online Social Networks.”
Ansolabehere, Stephen, John M. de Figueiredo, and James M. Snyder. 2003. β€œWhy Is There so Little Money in U.S. Politics?” The Journal of Economic Perspectives 17 (1): 105–30.
Arif, Ahmer, Leo Graiden Stewart, and Kate Starbird. 2018. β€œActing the Part: Examining Information Operations Within #BlackLivesMatter Discourse.” Proc. ACM Hum.-Comput. Interact. 2 (CSCW): 20:1–27.
Bail, Christopher Andrew. 2016. β€œCombining Natural Language Processing and Network Analysis to Examine How Advocacy Organizations Stimulate Conversation on Social Media.” Proceedings of the National Academy of Sciences, September, 201607151.
Baldassarri, Delia, and Guy Grossman. 2013. β€œThe Effect of Group Attachment and Social Position on Prosocial Behavior. Evidence from Lab-in-the-Field Experiments.” Edited by Angel SΓ‘nchez. PLoS ONE 8 (3): e58750.
Baldwin-Philippi, Jessica. 2017. β€œThe Myths of Data-Driven Campaigning.” Political Communication 34 (4): 627–33.
Bareinboim, Elias, and Judea Pearl. 2016. β€œCausal Inference and the Data-Fusion Problem.” Proceedings of the National Academy of Sciences 113 (27): 7345–52.
Bareinboim, Elias, Jin Tian, and Judea Pearl. 2014. β€œRecovering from Selection Bias in Causal and Statistical Inference.” In AAAI, 2410–16.
Battaglini, Marco, and Eleonora Patacchini. 2019. β€œSocial Networks in Policy Making.” Annual Review of Economics 11 (1): 473–94.
Benkler, Yochai, Rob Faris, and Harold Roberts. 2018. Network propaganda: manipulation, disinformation, and radicalization in American politics. New York, NY: Oxford University Press.
Bergemann, Dirk, and Alessandro Bonatti. 2019. β€œMarkets for Information: An Introduction.” Annual Review of Economics 11 (1): 85–107.
Bonchi, Francesco, Francesco Gullo, Bud Mishra, and Daniele Ramazzotti. 2018. β€œProbabilistic Causal Analysis of Social Influence.” In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 1003–12. CIKM ’18. New York, NY, USA: ACM.
Bond, Robert M., Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle, and James H. Fowler. 2012. β€œA 61-Million-Person Experiment in Social Influence and Political Mobilization.” Nature 489 (7415): 295–98.
Bradshaw, S., and P. Howard. 2017. β€œTroops, Trolls and Troublemakers: A Global Inventory of Organized Social Media Manipulation” 2017.12.
Brodersen, Kay H., Fabian Gallusser, Jim Koehler, Nicolas Remy, and Steven L. Scott. 2015. β€œInferring Causal Impact Using Bayesian Structural Time-Series Models.” The Annals of Applied Statistics 9 (1): 247–74.
Broockman, David E., Joshua Kalla, and Jasjeet S. Sekhon. 2016. β€œThe Design of Field Experiments With Survey Outcomes: A Framework for Selecting More Efficient, Robust, and Ethical Designs.” SSRN Scholarly Paper ID 2742869. Rochester, NY: Social Science Research Network.
Bullock, John G., Alan S. Gerber, Seth J. Hill, and Gregory A. Huber. 2013. β€œPartisan Bias in Factual Beliefs about Politics.” Working Paper 19080. National Bureau of Economic Research.
Bursztyn, Victor S, and Larry Birnbaum. 2019. β€œThousands of Small, Constant Rallies: A Large-Scale Analysis of Partisan WhatsApp Groups,” 6.
Carson, Andrea, Aaron J. Martin, and Shaun Ratcliff. 2019. β€œNegative Campaigning, Issue Salience and Vote Choice: Assessing the Effects of the Australian Labor Party’s 2016 β€˜Mediscare’ Campaign.” Journal of Elections, Public Opinion and Parties 0 (0): 1–22.
Cheng, Justin, Michael Bernstein, Cristian Danescu-Niculescu-Mizil, and Jure Leskovec. n.d. β€œAnyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions.”
Crawford, Vincent P, and Joel Sobel. 1982. β€œStrategic Information Transmission.” Econometrica: Journal of the Econometric Society 50 (6): 1431–51.
Degroot, Morris H. 1974. β€œReaching a Consensus.” Journal of the American Statistical Association 69 (345): 118–21.
Denizet-lewis, Benoit. 2016. β€œHow Do You Change Voters’ Minds? Have a Conversation.” The New York Times, April 7, 2016.
Evans, David S. 2017. β€œThe Economics of Attention Markets.” SSRN Scholarly Paper ID 3044858. Rochester, NY: Social Science Research Network.
Feinberg, Matthew, and Robb Willer. 2015. β€œFrom Gulf to Bridge When Do Moral Arguments Facilitate Political Influence?” Personality and Social Psychology Bulletin 41 (12): 1665–81.
Feuerverger, Andrey, Yu He, and Shashi Khatri. 2012. β€œStatistical Significance of the Netflix Challenge.” Statistical Science 27 (2): 202–31.
Forbes, Jeremy, Dianne Cook, and Rob J. Hyndman. 2020. β€œSpatial Modelling of the Two-Party Preferred Vote in Australian Federal Elections: 2001–2016.” Australian & New Zealand Journal of Statistics 62 (2): 168–85.
Gao, Yuxiang, Lauren Kennedy, Daniel Simpson, and Andrew Gelman. 2019. β€œImproving Multilevel Regression and Poststratification with Structured Priors.” arXiv:1908.06716 [Stat], August.
Gelman, Andrew. 2007. β€œStruggles with Survey Weighting and Regression Modeling.” Statistical Science 22 (2): 153–64.
Gelman, Andrew, and John B. Carlin. 2000. β€œPoststratification and Weighting Adjustments.” In In. Wiley.
Ghitza, Yair, and Andrew Gelman. 2013. β€œDeep Interactions with MRP: Election Turnout and Voting Patterns Among Small Electoral Subgroups.” American Journal of Political Science 57 (3): 762–76.
Goel, Sharad, Ashton Anderson, Jake Hofman, and Duncan J. Watts. 2015. β€œThe Structural Virality of Online Diffusion.” Management Science, July, 150722112809007.
Goel, Sharad, Jake M. Hofman, SΓ©bastien Lahaie, David M. Pennock, and Duncan J. Watts. 2010. β€œPredicting Consumer Behavior with Web Search.” Proceedings of the National Academy of Sciences 107 (41): 17486–90.
Goel, Sharad, Winter Mason, and Duncan J. Watts. 2010. β€œReal and Perceived Attitude Agreement in Social Networks.” Journal of Personality and Social Psychology 99 (4): 611–21.
Granovetter, Mark. 1983. β€œThe Strength of Weak Ties: A Network Theory Revisited.” Sociological Theory 1 (1): 201–33.
Granovetter, Mark S. 1973. β€œThe Strength of Weak Ties.” The American Journal of Sociology 78 (6): 1360–80.
Huang, Yuxiao, and Samantha Kleinberg. 2015. β€œFast and Accurate Causal Inference from Time Series Data.” In, 6.
JordΓ , Γ’scar, Katharina Knoll, Dmitry Kuvshinov, Moritz Schularick, and Alan M. Taylor. 2019. β€œThe Rate of Return on Everything, 1870–2015.” The Quarterly Journal of Economics 134 (3): 1225–98.
Karpf, David. 2018. β€œAnalytic Activism and Its Limitations.” Social Media + Society 4 (1): 2056305117750718.
Kellow, Christine L., and H. Leslie Steeves. 1998. β€œThe Role of Radio in the Rwandan Genocide.” Journal of Communication 48 (3): 107–28.
Kennedy, Edward H., Jacqueline A. Mauro, Michael J. Daniels, Natalie Burns, and Dylan S. Small. 2019. β€œHandling Missing Data in Instrumental Variable Methods for Causal Inference.” Annual Review of Statistics and Its Application 6 (1): 125–48.
King, Gary, Jennifer Pan, and Margaret E. Roberts. 10000. β€œHow the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument.” American Political Science Review.
Kohler, Ulrich, Frauke Kreuter, and Elizabeth A. Stuart. 2019. β€œNonprobability Sampling and Causal Analysis.” Annual Review of Statistics and Its Application 6 (1): 149–72.
Kulkarni, V. 2016. β€œTemporal Evolution of Social Innovation: What Matters?” SIAM Journal on Applied Dynamical Systems, January, 1485–1500.
Lee, Eun, Fariba Karimi, Hang-Hyun Jo, Markus Strohmaier, and Claudia Wagner. 2017. β€œHomophily Explains Perception Biases in Social Networks.” arXiv:1710.08601 [Physics], October.
Lerman, Kristina. 2017. β€œComputational Social Scientist Beware: Simpson’s Paradox in Behavioral Data.” arXiv:1710.08615 [Physics], October.
Lerman, Kristina, Xiaoran Yan, and Xin-Zeng Wu. 2016. β€œThe β€˜Majority Illusion’ in Social Networks.” PLOS ONE 11 (2): e0147617.
Levy, Gilat, and Ronny Razin. 2019. β€œEcho Chambers and Their Effects on Economic and Political Outcomes.” Annual Review of Economics 11 (1): 303–28.
Lewis, Rebecca. n.d. β€œBroadcasting the Reactionary Right on YouTube,” 61.
Little, R. J. A. 1993. β€œPost-Stratification: A Modeler’s Perspective.” Journal of the American Statistical Association 88 (423): 1001–12.
Little, Roderick JA. 1991. β€œInference with Survey Weights.” Journal of Official Statistics 7 (4): 405.
Lyons, Russell. 2011. β€œThe Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis.” Statistics, Politics, and Policy 2 (1).
Machado, Caio, Beatriz Kira, Vidya Narayanan, Bence Kollanyi, and Philip Howard. 2019. β€œA Study of Misinformation in WhatsApp Groups with a Focus on the Brazilian Presidential Elections.” In Companion Proceedings of The 2019 World Wide Web Conference, 1013–19. WWW ’19. New York, NY, USA: ACM.
Noel, Hans, and Brendan Nyhan. 2011. β€œThe β€˜Unfriending’ Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence.” Social Networks 33 (3): 211–18.
Noelle-Neumann, Elisabeth. 1974. β€œThe Spiral of Silence A Theory of Public Opinion.” Journal of Communication 24 (2): 43–51.
Open Science Collaboration. 2015. β€œEstimating the Reproducibility of Psychological Science.” Science 349 (6251): aac4716.
Persily, Nathaniel. 2017. β€œCan Democracy Survive the Internet?” Journal of Democracy 28 (2): 63–76.
Redlawsk, David P., Andrew J. W. Civettini, and Karen M. Emmerson. 2010. β€œThe Affective Tipping Point: Do Motivated Reasoners Ever β€˜Get It’?” Political Psychology 31 (4): 563–93.
Ribeiro, Manoel Horta, Raphael Ottoni, Robert West, VirgΓ­lio A. F. Almeida, and Wagner Meira. 2019. β€œAuditing Radicalization Pathways on YouTube.” arXiv:1908.08313 [Cs], August.
Rijt, Arnout van de, Idil Akin, Robb Willer, and Matthew Feinberg. 2016. β€œSuccess-Breeds-Success in Collective Political Behavior: Evidence from a Field Experiment.” Sociological Science 3: 940–50.
Rocher, Luc, Julien M. Hendrickx, and Yves-Alexandre de Montjoye. 2019. β€œEstimating the Success of Re-Identifications in Incomplete Datasets Using Generative Models.” Nature Communications 10 (1): 3069.
Rubin, Donald B, and Richard P Waterman. 2006. β€œEstimating the Causal Effects of Marketing Interventions Using Propensity Score Methodology.” Statistical Science 21 (2): 206–22.
Salganik, Matthew J., and Duncan J. Watts. 2008. β€œLeading the Herd Astray: An Experimental Study of Self-Fulfilling Prophecies in an Artificial Cultural Market.” Social Psychology Quarterly 74 (4): 338.
Sarigol, Emre, David Garcia, and Frank Schweitzer. 2014. β€œOnline Privacy As a Collective Phenomenon.” In Proceedings of the Second ACM Conference on Online Social Networks, 95–106. COSN ’14. New York, NY, USA: ACM.
Schuchard, Ross, Andrew T. Crooks, Anthony Stefanidis, and Arie Croitoru. 2019. β€œBot Stamina: Examining the Influence and Staying Power of Bots in Online Social Networks.” Applied Network Science 4 (1): 1–23.
Shalizi, Cosma Rohilla, and Edward McFowland III. 2016. β€œControlling for Latent Homophily in Social Networks Through Inferring Latent Locations.” arXiv:1607.06565 [Physics, Stat], July.
Shalizi, Cosma Rohilla, and Andrew C. Thomas. 2011. β€œHomophily and Contagion Are Generically Confounded in Observational Social Network Studies.” Sociological Methods & Research 40 (2): 211–39.
Stewart, Leo G, Ahmer Arif, and Kate Starbird. 2018. β€œExamining Trolls and Polarization with a Retweet Network,” 6.
Taleb, Nassim Nicholas. 2018. β€œElection Predictions as Martingales: An Arbitrage Approach.” Quantitative Finance 18 (1): 1–5.
Tan, Chenhao, Vlad Niculae, Cristian Danescu-Niculescu-Mizil, and Lillian Lee. 2016. β€œWinning Arguments: Interaction Dynamics and Persuasion Strategies in Good-Faith Online Discussions.” In Proceedings of the 25th International Conference on World Wide Web, 613–24. WWW ’16. Republic and Canton of Geneva, Switzerland: International World Wide Web Conferences Steering Committee.
Treisman, Daniel. 2017. β€œDemocracy by Mistake.” Working Paper 23944. National Bureau of Economic Research.
Wang, Wei, David Rothschild, Sharad Goel, and Andrew Gelman. 2015. β€œForecasting Elections with Non-Representative Polls.” International Journal of Forecasting 31 (3): 980–91.
Watts, D. J. 2007. β€œIs Justin Timberlake a Product of Cumulative Advantage?\(}\).” New York Times, April 15, 2007.
Watts, Duncan J., and Peter Sheridan Dodds. 2007. β€œInfluentials, Networks, and Public Opinion Formation.” Journal of Consumer Research 34 (4): 441–58.
Watts, Duncan J, and Steven H Strogatz. 1998. β€œCollective Dynamics of β€˜Small-World’ Networks.” Nature 393 (6684): 440–42.
Yadav, Pranjul, Lisiane Prunelli, Alexander Hoff, Michael Steinbach, Bonnie Westra, Vipin Kumar, and Gyorgy Simon. 2016. β€œCausal Inference in Observational Data.” arXiv:1611.04660 [Cs, Stat], November.
Yang, Shuang-Hong, Bo Long, Alex Smola, Narayanan Sadagopan, Zhaohui Zheng, and Hongyuan Zha. 2011. β€œLike Like Alike: Joint Friendship and Interest Propagation in Social Networks.” In Proceedings of the 20th International Conference on World Wide Web, 537–46. WWW ’11. New York, NY, USA: ACM.
Zarezade, Ali, Utkarsh Upadhyay, Hamid R. Rabiee, and Manuel Gomez-Rodriguez. 2017. β€œRedQueen: An Online Algorithm for Smart Broadcasting in Social Networks.” In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 51–60. WSDM ’17. New York, NY, USA: ACM Press.

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