Paper: A user-centric model of voting intention from Social Media

ACL ID P13-1098
Title A user-centric model of voting intention from Social Media
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

Social Media contain a multitude of user opinions which can be used to predict real- world phenomena in many domains in- cluding politics, finance and health. Most existing methods treat these problems as linear regression, learning to relate word frequencies and other simple features to a known response variable (e.g., voting intention polls or financial indicators). These techniques require very careful fil- tering of the input texts, as most Social Media posts are irrelevant to the task. In this paper, we present a novel approach which performs high quality filtering au- tomatically, through modelling not just words but also users, framed as a bilin- ear model with a sparse regulariser. We also consider the problem of modelling groups of related output variables, us- ing a structured mu...