A social-event based approach to sentiment analysis of identities and behaviors in text
Kenneth Joseph, Wei Wei, Matthew Benigni, Kathleen M. Carley · Journal of Mathematical Sociology · 2016
Kenneth Josepha*, Wei Weia, Matthew Benignia & Kathleen M. Carleyaa Societal Computing Program, Carnegie Mellon University, Pittsburgh, Pennsylvania, USACONTACT Kenneth Joseph [email protected] Societal Computing Program, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213.ABSTRACTWe 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.