Sentiment Polarity Identification in Financial News: A Cohesion-based Approach
Citation:
Ann Devitt and Khurshid Ahmad, Sentiment Polarity Identification in Financial News: A Cohesion-based Approach, Annual Meeting of the Association of Computational Linguistics (ACL 2007), Prague, Czech Republic, 25-27 June, 2007Download Item:

Abstract:
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, impacting 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 quantitative analysis of news sentiment impact on financial markets. Results from a preliminary evaluation are presented and discussed.
Author's Homepage:
http://people.tcd.ie/devittanhttp://people.tcd.ie/kahmad
Description:
PUBLISHEDPrague, Czech Republic
Author: Devitt, Ann; AHMAD, KHURSHID
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Annual Meeting of the Association of Computational Linguistics (ACL 2007)Type of material:
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Full text availableKeywords:
Sentiment Analysis, Lexical CohesionSubject (TCD):
Intelligent Content & CommunicationsLicences: