Pedro Mata, João Xavier Rita, Anabela Batista, João Xavier Rita
Sentiment Analysis (SA) or Opinion Mining (OM) is the field of study for a broader topic of Natural Language Processing. SA seeks to understand people's opinions, feelings, assessments, attitudes and emotions through text to generate knowledge and relevant information on a particular subject, in the business world with a greater focus on understanding the evaluation of products. We can often resume to an interpretation of attitude behind the text whether it is positive, negative or neutral. The growing importance of SA coincides with the growth of social networks, opinions, criticism, forum discussions, and blogs, among others. With this exponential evolution of data has arisen the need to apply SA in almost all social and commercial domains, because opinions are key in almost all activities and are one of the influencing factors in human and social behaviors, beliefs and perceptions of our own choices. As the opinion is one of the main influencing factors in the people's choice has made the spectrum of analysis broader for organizations making this a very relevant topic these days. This paper revealed that although there some advances for algorithms, techniques and frameworks to help SA implementations there is still a gap towards identifying benefits for business applications.