When social computing meets soft computing: opportunities and insights
Human-Centric Computing and Information Sciences
Introduction Social media are computer-mediated tools that allow people to create, share or exchange information, ideas, pictures, audio or videos in virtual communities by using open Internet. Among online social networking services, there exist very interesting and challengeable research works on how to improve an efficient social media computing and how to make an effective social network analysis and mining from the perspectives of both academia and industry. Therefore, social computing, as
... a research discipline, is emerging for handling those kind of data generated from social media. Normally, various social computing related techniques include statistical approaches, graph based approaches and so forth. However, a human nature is present in the social networks. This implies that the social networks are human-like-full of imprecise relations and connections between individuals, vague terms, groups and individuals with indefinite descriptions and characteristics of interests  . In order to better cope with these burning issues, advances on soft computing technologies, such as fuzzy set, formal concept analysis and rough set theories, probabilistic computing, as well as neural network and system, are paving a road to more valuable and feasible solutions to the emerging social media and big data, finally bringing a brilliant future of wisdom and intelligent social media network. This survey will be carried out for SNA from following various aspects, i.e., Abstract The characteristics of the massive social media data, diverse mobile sensing devices as well as the highly complex and dynamic user's social behavioral patterns have led to the generation of huge amounts of high dimension, uncertain, imprecision and noisy data from social networks. Thanks to the emerging soft computing techniques which unlike the conventional hard computing. It is widely used for coping with the tolerant of imprecision, uncertainty, partial truth, and approximation. One of the most important and promising applications is social network analysis (SNA) that is the process of investigating social structures and relevant properties through the use of network and graph theories. This paper aims to survey various SNA approaches using soft computing techniques such as fuzzy logic, formal concept analysis, rough sets theory and soft set theory. In addition, the relevant software packages about SNA are clearly summarized.