Work

Computational Text Analysis for Social Science: Model Assumptions and Complexity

Year: 2018

Type: article

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.

Source: Figshare

DOI: 10.1184/r1/6473291

Authors: O'Connor, Brendan, Bamman, David, A. Smith, Noah

Institution: Carnegie Mellon University

Language: English

Topic: Computational and Text Analysis Methods

Subfield: General Social Sciences

Field: Social Sciences

Domain: Social Sciences

Open Access status: green

Funder: National Science Foundation

Awards: CAREER: Flexible Learning for Natural Language Processing, RI-Small: Probabilistic Models for Structure Discovery in Text