Paper: A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge

ACL ID P09-1028
Title A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

Sentiment classi cation refers to the task of automatically identifying whether a given piece of text expresses positive or negative opinion towards a subject at hand. The proliferation of user-generated web content such as blogs, discussion forums and online review sites has made it possi- ble to perform large-scale mining of pub- lic opinion. Sentiment modeling is thus becoming a critical component of market intelligence and social media technologies that aim to tap into the collective wis- dom of crowds. In this paper, we consider the problem of learning high-quality senti- ment models with minimal manual super- vision. We propose a novel approach to learn from lexical prior knowledge in the form of domain-independent sentiment- laden terms, in conjunction with domain- dependent unlabel...