Automated Quantitative Content Analysis

Automated content analysis is becoming increasingly popular for large-scale inference of information from all kinds of text. Although the talk focuses on the estimation of policy positions from political text, the underlying methods are basically applicable to a large variety of research questions. 

Resources:

Grimmer, J. and Stewart, B. (2012): Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts. Forthcoming, Political Analysis.

Laver, M., Benoit, K., and Garry, J. (2003). Estimating the policy positions of political actors using words as data. American Political Science Review, 97(2):311–331.

Quinn, K. M., Monroe, B. L., Colaresi, M., Crespin, M., and Radev, D. R. (2010). "How To Analyze Political Attention With Minimal Assumptions And Costs"  American Journal of Politicial Science 54(1): 209–228.

Slapin, J. and Proksch, S.-O. (2008). A scaling model for estimating time series policy positions from texts. American Journal of Political Science, 52(8).