http://lattes.cnpq.br/5729800124276465; ALVES, André Luiz Firmino.
Resumo:
The dissemination of social communication means on the Web, such as blogs, discussion
forums, product evaluation sites, microblogs and social networks, provides a never before
seen volume of opinionative data in digital format. Not structured in its majority, this amount of data, has brought several challenges and opportunities for the academic community and the business world, considering the need for understanding, in an automatic form, people’s sentiments concerning a product, a service or even other people or facts, in order to facilitate the decision making process. In the recent years, several scientific contributions to solve sentiment analysis related problems were suggested. However, only a few of them consider the spatial-temporal factor, which is the geographical location of the information source or even of the information itself, as well as the possible opinion changes throughout time. The works that consider the spatial factor often assume the messages are already geocoded.
However, it could be a problem, since only a few information sources provide georeferenced messages. In this context, this work proposes a sentiment analysis approach which explores the spatial-temporal factor in order to better summarize the sentiments detected in a great amount of microtexts obtained from the Web. The approach uses Geographic Information Retrieval (GIR) and Sentiment Analysis techniques for the detection of geographic locations and sentiment polarity through textual evidences contained in the microtexts. The spatialtemporal analysis enables the visualization of sentiment changes which occurred in several geographic regions throughout the analyzed time period.