Text analysis is a prominently used approach from computational social science. In this episode, we examine three recent studies closely, that are using text analysis in interesting and constructive ways.

Text is a rich medium reflecting cultural and political concepts, ideas, agendas, tactics, events, and power structures of the time. Large text corpora open windows and allow comparisons across countries, cultures, and time. Different types of text contain representations of different slices of culture, politics, and social life. They therefor are of interest to various subfields in the social sciences and humanities. By collecting and preparing for analysis large text corpora scholars can access and make available vast troves of knowledge on various questions and in different subfields. The tremendous collective efforts in digitizing and making available text corpora are a massive accelerating factor in this effort. Let's have a closer look.

Chapters:

00:00 - Introduction
00:22 - Text analysis in political science
05:43 - Making sense of party competition during the 2015 refugee crisis with a bag of words
11:51 - Who lives in the past, the present, or the future? A supervised learning approach
15:48 - Political innovation in the French Revolution
22:15 - Conclusion

Script to episode with references and further readings:

http://digitalmedia.andreasjungherr.de/css.html#text-analysis-typical-approaches-in-computational-social-science-1