Analysis of Fuzzy Logic based Textual Meaning Inference Approach for Comment Content Estimation in Social Networks

Abstract

In recent years, social networking has become a very popular communication tool among internet users connected by one or more relationships. Thousands or even millions of users share their experiences and opinions on different aspects of life everyday through social networking communities. The positive or negative content of the comments posted by the members of the social network can arouse great interest among the members of the social network group. Understanding social networks requires the analysis of structural relationships and interaction patterns between users. In this paper, an analysis of fuzzy logic based textual meaning inference analysis was performed for the estimation of content in social networks. The positive comments made by the members on the social networks have the positive effect for the users to read comments. In this context, our semantic inference approach is analyzed with the help of fuzzy logic where the content of comment can be positive or negative. According to the input values in the fuzzy logic system, the relevant interpretation can be positive or negative. Considering that the results of the obtained system yields highly accurate results, we think that our fuzzy logic based semantic inference approach can be used in many social networks.WOS:00054527870001