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Automatic Sentiment Analysis on Web Texts for Competitive Intelligence

Automatic Sentiment Analysis on Web Texts for Competitive Intelligence
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Author(s): Stanley Loh (Lutheran University of Brasil (ULBRA), Brazil & Technology Faculty Senac Pelotas, Brazil), Fabiana Lorenzi (Lutheran University of Brasil (ULBRA), Brazil), Paulo Roberto Pasqualotti (University FEEVALE, Brazil), Sabrina Ferreira Rodrigues (Lutheran University of Brasil (ULBRA), Brazil), Luis Fernando Fortes Garcia (Lutheran University of Brasil (ULBRA), Brazil & Dom Bosco Faculty of Porto Alegre, Brazil) and Valesca Persch Reichelt (Lutheran University of Brasil (ULBRA), Brazil)
Copyright: 2013
Pages: 11
Source title: Advancing Information Management through Semantic Web Concepts and Ontologies
Source Author(s)/Editor(s): Patricia Ordóñez de Pablos (Universidad de Oviedo, Spain), Héctor Oscar Nigro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina), Robert D. Tennyson (University of Minnesota, USA), Sandra Elizabeth Gonzalez Cisaro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina) and Waldemar Karwowski (University of Central Florida, USA)
DOI: 10.4018/978-1-4666-2494-8.ch017

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Abstract

This chapter presents a software tool that helps the Competitive Intelligence process by collecting and analyzing texts published on the Internet. The goal is to automatically analyze indicators of the sentiment present in texts about a certain theme, whether positive or negative. The sentiment analysis is made through a probabilistic process over keywords present in the texts, using as reference a task ontology with positive and negative words defined with a degree of confidence.

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