文章基本信息

标题：Identifying Polarity in Financial Texts for Sentiment Analysis: A Corpus-based Approach
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作者：Antonio Moreno-Ortiz ; Antonio Moreno-Ortiz ; Javier Fernández-Cruz 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2015
卷号：198
页码：330-338
DOI：10.1016/j.sbspro.2015.07.451
语种：English
出版社：Elsevier
摘要：AbstractIn 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.
关键词：sentiment analysis;information retrieval;terminology;specialized languages;financial texts;corpus linguistics