Computational Text Analysis for Social Science: Model Assumptions and Complexity

Computational Text Analysis for Social Science: Model Assumptions and Complexity

Abstract

Across many disciplines, interest is increasing in the use of computational text analysis in the service of social science questions. We survey the spectrum of current methods, which lie on two dimensions: (1) computational and statistical model complexity; and (2) domain assumptions. This comparative perspective suggests directions of research to better align new methods with the goals of social scientists.

(Brendan T. O'Connor, David Bamman, Noah A. Smith)

https://people.cs.umass.edu/~wallach/workshops/nips2011css/papers/OConnor.pdf

https://www.semanticscholar.org/paper/Computational-Text-Analysis-for-Social-Science%3A-and-O%27Connor-Bamman/f51239038357c6357bbb2f6d4d98b8c48881a43d