RT Journal Article
T1 Identifying polarity in financial texts for sentiment analysis: a corpus-based approach
A1 Moreno-Ortiz, Antonio Jesús
A1 Fernández Cruz, Javier
K1 Lingüística computacional
K1 Recuperación de la información
AB 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.
PB Elsevier
YR 2015
FD 2015
LK https://hdl.handle.net/10630/39527
UL https://hdl.handle.net/10630/39527
LA eng
NO 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.
NO This work has been sponsored by the Spanish Government under grant FFI2011-25893 (Lingmotif project, http://tecnolengua.uma.es/lingmotif
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026