A social-event based approach to sentiment analysis of identities and behaviors in text. Issue 3 (2nd July 2016)

• Record Type: Journal Article
• Authors: Joseph, Kenneth; Wei, Wei; Benigni, Matthew; Carley, Kathleen M.
• Is Part Of: Journal of mathematical sociology. Volume 40:Issue 3(2016)
• Page Start: 137
• Page End: 166
• Publication Date: 2016-07-02
• Subjects: Affect control theory -- Arab Spring -- Bayesian inference -- machine learning -- natural language processing -- sentiment analysis; Sociology -- Periodicals; Sociology -- Mathematical models -- Periodicals; 301.0151
• DOI: 10.1080/0022250X.2016.1159206
• Languages: English
• ISSNs: 0022-250X

Abstract

ABSTRACT: We describe a new methodology to infer sentiments held toward identities and behaviors from social events that we extract from a large corpus of newspaper text. Our approach draws on affect control theory, a mathematical model of how sentiment is encoded in social events and culturally shared views toward identities and behaviors. While most sentiment analysis approaches evaluate concepts on a single, evaluative dimension, our work extracts a three-dimensional sentiment "profile" for each concept. We can also infer when multiple sentiment profiles for a concept are likely to exist. We provide a case study of a large newspaper corpus on the Arab Spring, which helps to validate our approach.