Paper: Extracting Social Power Relationships from Natural Language

ACL ID P11-1078
Title Extracting Social Power Relationships from Natural Language
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011

Sociolinguists have long argued that social context influences language use in all manner of ways, resulting in lects 1. This paper ex- plores a text classification problem we will call lect modeling, an example of what has been termed computational sociolinguistics. In particular, we use machine learning techniques to identify social power relationships between members of a social network, based purely on the content of their interpersonal communica- tion. We rely on statistical methods, as op- posed to language-specific engineering, to extract features which represent vocabulary and grammar usage indicative of social power lect. We then apply support vector machines to model the social power lects representing su- perior-subordinate communication in the En- ron email corpus....