Week 10
Using Text to Measure Ideology - Scaling
Topics
- What are scaling models and what can they tell us?
- Can we represent politicians/users ideology using text?
Readings
Required Readings
Laver, Michael, Kenneth Benoit, and John Garry. 2003. “Extracting Policy Positions from Political Texts Using Words as Data”. American Political Science Review. 97, 2, 311-331
Slapin, Jonathan and Sven-Oliver Prokschk. 2008. “A Scaling Model for Estimating Time-Series Party Positions from Texts.” American Journal of Political Science. 52, 3 705-722
Non-Required Readings
Barberá, Pablo. “Birds of the same feather tweet together: Bayesian ideal point estimation using Twitter data.” Political analysis 23, no. 1 (2015): 76-91.Harvard
Aruguete, Natalia, Ernesto Calvo, and Tiago Ventura. “News by popular demand: Ideological congruence, issue salience, and media reputation in news sharing.” The International Journal of Press/Politics 28, no. 3 (2023): 558-579.
Rheault, Ludovic, and Christopher Cochrane. “Word embeddings for the analysis of ideological placement in parliamentary corpora.” Political Analysis 28, no. 1 (2020): 112-133.
Izumi, Mauricio Y., and Danilo B. Medeiros. “Government and opposition in legislative speechmaking: using text-as-data to estimate Brazilian political parties’ policy positions.” Latin American Politics and Society 63, no. 1 (2021): 145-164.
Coding Materials