Identifying Polarity in Financial Texts for Sentiment Analysis: A Corpus-based Approach | Zendy

Antonio Moreno Ortiz | Zendy; Javier Fernández-Cruz | Zendy

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Identifying Polarity in Financial Texts for Sentiment Analysis: A Corpus-based Approach

Author(s) -

Antonio Moreno Ortiz,

Javier Fernández-Cruz

Publication year - 2015

Publication title -

procedia - social and behavioral sciences

Language(s) - English

Resource type - Journals

ISSN - 1877-0428

DOI - 10.1016/j.sbspro.2015.07.451

Subject(s) - polarity (international relations) , computer science , lexicon , sentiment analysis , natural language processing , artificial intelligence , domain (mathematical analysis) , measure (data warehouse) , data mining , mathematics , chemistry , mathematical analysis , biochemistry , cell

In this paper we describe our methodology to integrate domain-specific sentiment analysis in a lexicon-based system initially designed for general language texts. Our approach to dealing with specialized domains is based on the idea of “plug-in” lexical resources which can be applied on demand. A simple 3-step model based on the weirdness ratio measure is proposed to extract candidate terms from specialized corpora, which are then matched against our existing general-language polarity database to obtain sentiment-bearing words whose polarity is domain-specific

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