Social Network and Sentiment Analysis on Twitter: Towards a Combined Approach

Twitter is a platform which may contain opinions, thoughts, facts and other information. Within it, many and various communities are originated by users with common interests, or with similar ways to feel part of the community. This paper presents a possible combined approach between Social Network Analysis and Sentiment Analysis. In particular, we have tried to associate a sentiment to the nodes of the graphs showing the social connections, and this may highlight the potential correlations. The idea behind it is that, on the one hand, the network topology can contextualize and then, in part, unmask some incorrect results of the Sentiment Analysis; on the other hand, the polarity of the feeling on the network can highlight the role of semantic connections in the hierarchy of the communities that are present in the network. In this work, we illustrate the approach to the issue, together with the system architecture and, then, we discuss our first results.