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  • 标题:Identifying Polarity in Financial Texts for Sentiment Analysis: A Corpus-based Approach
  • 本地全文:下载
  • 作者:Antonio Moreno-Ortiz ; Antonio Moreno-Ortiz ; Javier Fernández-Cruz
  • 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
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