Companies image evaluation using social media and sentiment analysis

While the literature contains many slightly different definitions for the image of a company, they all put great emphasis on its importance. Many of the messages posted on social media networks nowadays contain strong sentiment and emotion indications regarding almost any topic, therefore turning them into a rich and almost real-time data source for analyzing the public’s opinion on various subjects, including many of the factors that can influence the image of companies. Thus, in this chapter we propose a natural language processing (NLP) approach for monitoring and evaluating the companies’ image by extracting information from social media messages posted on Twitter. The messages are analyzed using a bag-of-words sentiment analysis approach. The results of the analysis are stored as semantically structured data, thus making it possible to fully exploit the possibilities offered by semantic web technologies, such as inference and accessing the vast amount of knowledge in Linked Open Data, for further analysis.