Sentiment Diffusion in Online Social Networks: A Survey from the Computational Perspective

With the development of mobile technologies, users can easily access Online social networks (OSNs), consequently, massive contents including personal experiences, observations, or opinions are generated online. These contents are being shared and exchanged in OSNs, which have a significant influence on the minds of people toward politics, societies, economics, etc. In this case, sentiment diffusion which focuses on how the process of information diffusion in OSNs is affected by sentiments has become an important issue. In this survey, we conduct a comprehensive review of the problem. Specifically, we first present the definition and classification of sentiment, introduce the most advanced computational sentiment analysis techniques, list their applications, and disclose available sentiment analysis resources. Then the main OSN components, functionalities, and structural features applied in modeling social networks are analyzed and summarized. Next, a thorough overview of the information diffusion technologies in OSNs, including graph and non-graph models is made. At last, a systematic and in-depth overview of the current state and issues of research on sentiment diffusion in OSNs is provided. This survey provides the necessary knowledge and new insights for relevant researchers to better understand the research state, remaining challenges, and future directions in this field.