Paper: Sentiment Polarity Identification in Financial News: A Cohesion-based Approach

ACL ID P07-1124
Title Sentiment Polarity Identification in Financial News: A Cohesion-based Approach
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

Text is not unadulterated fact. A text can make you laugh or cry but can it also make you short sell your stocks in company A and buy up options in company B? Research in the domain of finance strongly suggests that it can. Studies have shown that both the informational and affective aspects of news text affect the markets in profound ways, im- pacting on volumes of trades, stock prices, volatility and even future firm earnings. This paper aims to explore a computable metric of positive or negative polarity in financial news text which is consistent with human judgments and can be used in a quantita- tive analysis of news sentiment impact on fi- nancial markets. Results from a preliminary evaluation are presented and discussed.