LIWC-Based Sentiment Analysis in Spanish Product Reviews View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2014

AUTHORS

Estanislao López-López , María del Pilar Salas-Zárate , Ángela Almela , Miguel Ángel Rodríguez-García , Rafael Valencia-García , Giner Alor-Hernández

ABSTRACT

Opinion mining is the study of opinions and emotions of authors about specific topics on the Web. Opinion mining identifies whether the opinion about a given topic, expressed in a document, is positive or negative. Nowadays, with the exponential growth of social medial i.e. blogs and social networks, organizations and individual persons are increasingly using the number of reviews of these media for decision making about a product or service. This paper investigates technological products reviews mining using the psychological and linguistic features obtained through of text analysis software, LIWC. Furthermore, an analysis of the classification techniques J48, SMO, and BayesNet has been performed by using WEKA (Waikato Environment for Knowledge Analysis). This analysis aims to evaluate the classifying potential of the LIWC (Linguistic Inquiry and Word Count) dimensions on written opinions in Spanish. All in all, findings have revealed that the combination of the four LIWC dimensions provides better results than the other combinations and individual dimensions, and that SMO is the algorithm which has obtained the best results. More... »

PAGES

379-386

References to SciGraph publications

Book

TITLE

Distributed Computing and Artificial Intelligence, 11th International Conference

ISBN

978-3-319-07592-1
978-3-319-07593-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-07593-8_44

DOI

http://dx.doi.org/10.1007/978-3-319-07593-8_44

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1036925975


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