Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts
Stanford University · Princeton University · +2 more institutions
Abstract
Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have hindered their use in political science research. Here lies the promise of automated text analysis: it substantially reduces the costs of analyzing large collections of text. We provide a guide to this exciting new area of research and show how, in many instances, the methods have already obtained part of their promise. But there are pitfalls to using automated methods—they are no substitute for careful thought and close reading and require extensive and problem-specific validation. We survey a wide range of new…
Citation impact
- FWCI
- 1283.22
- Percentile
- 100%
- References
- 107
Authors
2Topics & keywords
- Computer science
- Politics
- Reading (process)
- Data science
- Content analysis
- Range (aeronautics)
- Information retrieval
- Social science
- Quality Education