Mineração de opiniões aplicada a mídias sociais

Abstract

The competitive environment has become more dynamic in the last few decades due to the great development of information and comunication technologies and to the globalization process.A company manager must, thus, always be well informed about the competitive landscape before making strategic decisions. In this sense, the Competitive Intelligence (CI) emerges as a discipline that aims to systematize the collection and analysis of information in the competitive environment willing to assist decision making. There is, however, an increasing amount of information being produced and released in Internet and traditional media, which become unwieldy. Associated with this, managers still suffer with time constraints to respond to the market stimuli and remain competitive. Thus, it is necessary to maintain a constant staff monitoring the competitive environment to be able to handle the amount of information from this various sources. We believe that the application Text Analysis techniques can help in various stages of such process. This work presents a proposal to use such techniques to aid the process of Competitive Intelligence. We discuss the use of Sentiment Analysis techniques coupled with Named Entity Recognition in texts from social media - especially Twitter - which helps in the analysis of the attitudes of the consumer market towards a brand. We also present a system implementing the proposed techniques, the evaluations made with it and present our conclusions.