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  • Küçük Resim
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    Analysis of Fuzzy Logic based Textual Meaning Inference Approach for Comment Content Estimation in Social Networks
    (Gazi Univ, 2020) Bayrakdar, Sumeyye; Yucedag, Ibrahim
    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.
  • Küçük Resim Yok
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    Exploiting 5G Enabled Cognitive Radio Technology for Semantic Analysis in Social Networks
    (Springer, 2023) Bayrakdar, Sumeyye; Yucedag, Ibrahim
    Cognitive radio is an intelligent communication system that is aware of its environment and can dynamically adapt its operating parameters with the aim of providing an efficient use of the scarce spectrum. The main advantage of cognitive radio technology is its ability to adapt and cooperate with all other wireless technologies such as fifth generation technology, 5G. 5G enabled cognitive radio technology provides accelerated communication performance in accordance with spectrum efficiency and energy efficiency. 5G enabled cognitive radio proposes system interoperability and integration of communication system through cognition. Social networking is a common communication media among internet users connected by one or more relationships. Large numbers of internet users share their experiences and thoughts through social networking web sites. Semantic analysis is defined as the process of drawing meaning from text. In this paper, a fuzzy logic based semantic analysis is performed for the estimation of comment content in 5G enabled cognitive radio based social networks. In social networks, the positive comments posted by the users have the positive influence for the members to examine related comments. The comment content posted by the users is decided to be positive or negative with the help of fuzzy logic based semantic analysis approach. In this regard, the relevant interpretation can be positive or negative based on the input parameters in the fuzzy logic system. Our 5G enabled cognitive radio technology based semantic analysis approach with fuzzy logic system can be utilized in many social networks, taking superior accuracy results of 93% into account.
  • Küçük Resim
    Öğe
    Semantic analysis on social networks: A survey
    (Wiley, 2020) Bayrakdar, Sumeyye; Yucedag, Ibrahim; Simsek, Mehmet; Dogru, Ibrahim Alper
    As social networks are getting more and more popular day by day, large numbers of users becoming constantly active social network users. In this way, there is a huge amount of data produced by users in social networks. While social networking sites and dynamic applications of these sites are actively used by people, social network analysis is also receiving an increasing interest. Moreover, semantic understanding of text, image, and video shared in a social network has been a significant topic in the network analysis research. To the best of the author's knowledge, there has not been any comprehensive survey of social networks, including semantic analysis. In this survey, we have reviewed over 200 contributions in the field, most of which appeared in recent years. This paper not only aims to provide a comprehensive survey of the research and application of social network analysis based on semantic analysis but also summarizes the state-of-the-art techniques for analyzing social media data. First of all, in this paper, social networks, basic concepts, and components related to social network analysis were examined. Second, semantic analysis methods for text, image, and video in social networks are explained, and various studies about these topics are examined in the literature. Then, the emerging approaches in social network analysis research, especially in semantic social network analysis, are discussed. Finally, the trending topics and applications for future directions of the research are emphasized; the information on what kind of studies may be realized in this area is given.