A framework for investigating the dynamics of user and community sentiments in a social platform

Social platforms are the preferred medium for many people to express their opinions on many topics. This has led many professionals from various fields (marketing, politics, research and development, etc.) to demand increasingly advanced approaches capable of analyzing the evolution of user or community sentiments on particular topics. In this paper, we want to make a contribution to addressing this issue. Specifically, we propose a model and a framework to analyze the dynamics of user and community sentiments in a social platform. In particular, our framework currently focuses on three activities, namely: (i) finding users capable of creating and maintaining a community that reflects their sentiment on a topic; (ii) studying how a user or community sentiment on a topic evolves over time; and (iii) investigating the cross-contamination between a user community and its neighborhood. We tested our framework by means of an extensive experimental campaign that we describe in the paper. Our framework is extremely scalable, and further activities can be easily implemented in it in the near future.