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Moreno-Ortiz, Antonio Jesús Fernández-Cruz, Javier 2025-07-28T09:21:00Z 2025-07-28T09:21:00Z 2015 Moreno-Ortiz, A., & Fernández-Cruz, J. (2015). Identifying Polarity in Financial Texts for Sentiment Analysis: A Corpus-based Approach. Procedia - Social and Behavioral Sciences, 198, 330–338. https://hdl.handle.net/10630/39527 10.1016/j.sbspro.2015.07.451 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. eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Lingüística computacional Recuperación de la información Identifying polarity in financial texts for sentiment analysis: a corpus-based approach journal article