Applied psephology

July 12, 2016 — May 25, 2022

Bayes
hidden variables
hierarchical models
insurgency
networks
regression
statistics
wonk

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Tom Gauld:

Figure 1: 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.

🏗 mention problems of ecological inference, Simpson’s paradoxes in electoral demographics, “Symbolic data analysis” for census data, response bias, survey design etc. Finish up with practical tips.

1 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)

2 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?

2.1 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 and most famously of all Antony Green, who uses Cunningham (1979) to call seats as election results come in.

3 On voters strategically changing electorates

What are the marginal benefits of treating politics like the pork-barrel 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 more likely to claim council seats as a side benefit.

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

4 Incoming

5 References

Acemoglu, Ozdaglar, and ParandehGheibi. 2010. “Spread of (Mis)information in Social Networks.” Games and Economic Behavior.
Achlioptas, Clauset, Kempe, et al. 2005. “On 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. STOC ’05.
Ansolabehere, de Figueiredo, and Snyder. 2003. “Why Is There so Little Money in U.S. Politics?” The Journal of Economic Perspectives.
Arif, Stewart, and Starbird. 2018. “Acting the Part: Examining Information Operations Within #BlackLivesMatter Discourse.” Proc. ACM Hum.-Comput. Interact.
Bail. 2016. “Combining Natural Language Processing and Network Analysis to Examine How Advocacy Organizations Stimulate Conversation on Social Media.” Proceedings of the National Academy of Sciences.
Baldassarri, and Grossman. 2013. “The Effect of Group Attachment and Social Position on Prosocial Behavior. Evidence from Lab-in-the-Field Experiments.” Edited by Angel Sánchez. PLoS ONE.
Baldwin-Philippi. 2017. “The Myths of Data-Driven Campaigning.” Political Communication.
Bareinboim, and Pearl. 2016. “Causal Inference and the Data-Fusion Problem.” Proceedings of the National Academy of Sciences.
Bareinboim, Tian, and Pearl. 2014. “Recovering from Selection Bias in Causal and Statistical Inference.” In AAAI.
Battaglini, and Patacchini. 2019. “Social Networks in Policy Making.” Annual Review of Economics.
Benkler, Faris, and Roberts. 2018. Network propaganda: manipulation, disinformation, and radicalization in American politics.
Bergemann, and Bonatti. 2019. “Markets for Information: An Introduction.” Annual Review of Economics.
Bonchi, Gullo, Mishra, et al. 2018. “Probabilistic Causal Analysis of Social Influence.” In Proceedings of the 27th ACM International Conference on Information and Knowledge Management. CIKM ’18.
Bond, Fariss, Jones, et al. 2012. “A 61-Million-Person Experiment in Social Influence and Political Mobilization.” Nature.
Bradshaw, and Howard. 2017. “Troops, Trolls and Troublemakers: A Global Inventory of Organized Social Media Manipulation.”
Brodersen, Gallusser, Koehler, et al. 2015. “Inferring Causal Impact Using Bayesian Structural Time-Series Models.” The Annals of Applied Statistics.
Broockman, David, and Kalla. 2020. “When and Why Are Campaigns’ Persuasive Effects Small? Evidence from the 2020 US Presidential Election.”
Broockman, David E., Kalla, and Sekhon. 2016. “The Design of Field Experiments With Survey Outcomes: A Framework for Selecting More Efficient, Robust, and Ethical Designs.” SSRN Scholarly Paper ID 2742869.
Bullock, Gerber, Hill, et al. 2013. “Partisan Bias in Factual Beliefs about Politics.” Working Paper 19080.
Bursztyn, and Birnbaum. 2019. “Thousands of Small, Constant Rallies: A Large-Scale Analysis of Partisan WhatsApp Groups.”
Carson, Martin, and Ratcliff. 2019. “Negative Campaigning, Issue Salience and Vote Choice: Assessing the Effects of the Australian Labor Party’s 2016 ‘Mediscare’ Campaign.” Journal of Elections, Public Opinion and Parties.
Cheng, Bernstein, Danescu-Niculescu-Mizil, et al. n.d. “Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions.”
Crawford, and Sobel. 1982. “Strategic Information Transmission.” Econometrica: Journal of the Econometric Society.
Cunningham. 1979. “Election Night Forecasting : Australian House of Representatives Elections.”
Degroot. 1974. “Reaching a Consensus.” Journal of the American Statistical Association.
Denizet-lewis. 2016. “How Do You Change Voters’ Minds? Have a Conversation.” The New York Times.
Evans. 2017. “The Economics of Attention Markets.” SSRN Scholarly Paper ID 3044858.
Feinberg, and Willer. 2015. “From Gulf to Bridge When Do Moral Arguments Facilitate Political Influence?” Personality and Social Psychology Bulletin.
Feuerverger, He, and Khatri. 2012. “Statistical Significance of the Netflix Challenge.” Statistical Science.
Forbes, Cook, and Hyndman. 2020. “Spatial Modelling of the Two-Party Preferred Vote in Australian Federal Elections: 2001–2016.” Australian & New Zealand Journal of Statistics.
Gao, Kennedy, Simpson, et al. 2019. “Improving Multilevel Regression and Poststratification with Structured Priors.” arXiv:1908.06716 [Stat].
Gelman. 2007. “Struggles with Survey Weighting and Regression Modeling.” Statistical Science.
Gelman, and Carlin. 2000. “Poststratification and Weighting Adjustments.” In In.
Ghitza, and Gelman. 2013. “Deep Interactions with MRP: Election Turnout and Voting Patterns Among Small Electoral Subgroups.” American Journal of Political Science.
Goel, Anderson, Hofman, et al. 2015. “The Structural Virality of Online Diffusion.” Management Science.
Goel, Hofman, Lahaie, et al. 2010. “Predicting Consumer Behavior with Web Search.” Proceedings of the National Academy of Sciences.
Goel, Mason, and Watts. 2010. “Real and Perceived Attitude Agreement in Social Networks.” Journal of Personality and Social Psychology.
Granovetter, Mark S. 1973. “The Strength of Weak Ties.” The American Journal of Sociology.
Granovetter, Mark. 1983. “The Strength of Weak Ties: A Network Theory Revisited.” Sociological Theory.
Huang, and Kleinberg. 2015. “Fast and Accurate Causal Inference from Time Series Data.” In.
Jordà, Knoll, Kuvshinov, et al. 2019. “The Rate of Return on Everything, 1870–2015.” The Quarterly Journal of Economics.
Karpf. 2018. “Analytic Activism and Its Limitations.” Social Media + Society.
Kellow, and Steeves. 1998. “The Role of Radio in the Rwandan Genocide.” Journal of Communication.
Kennedy, Mauro, Daniels, et al. 2019. “Handling Missing Data in Instrumental Variable Methods for Causal Inference.” Annual Review of Statistics and Its Application.
King, Pan, and Roberts. 10000. “How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument.” American Political Science Review.
Kohler, Kreuter, and Stuart. 2019. “Nonprobability Sampling and Causal Analysis.” Annual Review of Statistics and Its Application.
Kulkarni. 2016. “Temporal Evolution of Social Innovation: What Matters?” SIAM Journal on Applied Dynamical Systems.
Lee, Karimi, Jo, et al. 2017. “Homophily Explains Perception Biases in Social Networks.” arXiv:1710.08601 [Physics].
Lerman. 2017. “Computational Social Scientist Beware: Simpson’s Paradox in Behavioral Data.” arXiv:1710.08615 [Physics].
Lerman, Yan, and Wu. 2016. “The ‘Majority Illusion’ in Social Networks.” PLOS ONE.
Levy, and Razin. 2019. “Echo Chambers and Their Effects on Economic and Political Outcomes.” Annual Review of Economics.
Lewis. n.d. “Broadcasting the Reactionary Right on YouTube.”
Little, Roderick JA. 1991. “Inference with Survey Weights.” Journal of Official Statistics.
Little, R. J. A. 1993. “Post-Stratification: A Modeler’s Perspective.” Journal of the American Statistical Association.
Lyons. 2011. “The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis.” Statistics, Politics, and Policy.
Machado, Kira, Narayanan, et al. 2019. “A Study of Misinformation in WhatsApp Groups with a Focus on the Brazilian Presidential Elections.” In Companion Proceedings of The 2019 World Wide Web Conference. WWW ’19.
Maley, and Medew. 1991. “Some Approaches to Election Night Forecasting in Australia.” Australian Journal of Political Science.
Noelle-Neumann. 1974. “The Spiral of Silence A Theory of Public Opinion.” Journal of Communication.
Noel, and Nyhan. 2011. “The ‘Unfriending’ Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence.” Social Networks.
Open Science Collaboration. 2015. “Estimating the Reproducibility of Psychological Science.” Science.
Persily. 2017. “Can Democracy Survive the Internet?” Journal of Democracy.
Redlawsk, Civettini, and Emmerson. 2010. “The Affective Tipping Point: Do Motivated Reasoners Ever ‘Get It’?” Political Psychology.
Ribeiro, Ottoni, West, et al. 2019. “Auditing Radicalization Pathways on YouTube.” arXiv:1908.08313 [Cs].
Rocher, Hendrickx, and Montjoye. 2019. “Estimating the Success of Re-Identifications in Incomplete Datasets Using Generative Models.” Nature Communications.
Rubin, and Waterman. 2006. “Estimating the Causal Effects of Marketing Interventions Using Propensity Score Methodology.” Statistical Science.
Salganik, and Watts. 2008. “Leading the Herd Astray: An Experimental Study of Self-Fulfilling Prophecies in an Artificial Cultural Market.” Social Psychology Quarterly.
Sarigol, Garcia, and Schweitzer. 2014. “Online Privacy As a Collective Phenomenon.” In Proceedings of the Second ACM Conference on Online Social Networks. COSN ’14.
Schuchard, Crooks, Stefanidis, et al. 2019. “Bot Stamina: Examining the Influence and Staying Power of Bots in Online Social Networks.” Applied Network Science.
Shalizi, and McFowland III. 2016. “Controlling for Latent Homophily in Social Networks Through Inferring Latent Locations.” arXiv:1607.06565 [Physics, Stat].
Shalizi, and Thomas. 2011. “Homophily and Contagion Are Generically Confounded in Observational Social Network Studies.” Sociological Methods & Research.
Stewart, Arif, and Starbird. 2018. “Examining Trolls and Polarization with a Retweet Network.”
Taleb. 2018. “Election Predictions as Martingales: An Arbitrage Approach.” Quantitative Finance.
Tan, Niculae, Danescu-Niculescu-Mizil, et al. 2016. “Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-Faith Online Discussions.” In Proceedings of the 25th International Conference on World Wide Web. WWW ’16.
Treisman. 2017. “Democracy by Mistake.” Working Paper 23944.
van de Rijt, Akin, Willer, et al. 2016. “Success-Breeds-Success in Collective Political Behavior: Evidence from a Field Experiment.” Sociological Science.
Wang, Rothschild, Goel, et al. 2015. “Forecasting Elections with Non-Representative Polls.” International Journal of Forecasting.
Watts, D. J. 2007. “Is Justin Timberlake a Product of Cumulative Advantage?\(}\).” New York Times.
Watts, Duncan J., and Dodds. 2007. “Influentials, Networks, and Public Opinion Formation.” Journal of Consumer Research.
Watts, Duncan J, and Strogatz. 1998. “Collective Dynamics of ‘Small-World’ Networks.” Nature.
Yadav, Prunelli, Hoff, et al. 2016. “Causal Inference in Observational Data.” arXiv:1611.04660 [Cs, Stat].
Yang, Long, Smola, et al. 2011. “Like Like Alike: Joint Friendship and Interest Propagation in Social Networks.” In Proceedings of the 20th International Conference on World Wide Web. WWW ’11.
Zarezade, Upadhyay, Rabiee, et al. 2017. “RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks.” In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining. WSDM ’17.