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. In this survey, we have reviewed over 200 contributions in the field, most of which appeared in recent years. To the best of the author's knowledge, there has not been any comprehensive survey of social networks, including semantic analysis. Moreover, semantic understanding of text, image, and video shared in a social network has been a significant topic in the network analysis research. While social networking sites and dynamic applications of these sites are actively used by people, social network analysis is also receiving an increasing interest. In this way, there is a huge amount of data produced by users in social networks. Finally, subjects and opportunities for future research directions are explained.Īs social networks are getting more and more popular day by day, large numbers of users becoming constantly active social network users. Next, the evolving methods in research on social network analysis are discussed, especially in analyzing semantic text on social networks. Semantic ways of manipulating text in social networks are then clarified, and literature discusses studies before on these themes.

This research intentions to deliver an inclusive overview of social network research and application analyze state-of-the-art social media data analysis methods by reviewing basic concepts, social networks and elements social network research is linked to. Using social media, data analysis was primarily used for machine learning, analysis, information extraction, statistical modelling, data preprocessing, and data interpretation processes. Utilizing data processing provides vast datasets such as averages, laws, and patterns to discover practical knowledge. Semantic comprehension of the document, image, and video exchanged in a social network was also an essential topic in network analysis. social media sites handle an immense amount of knowledge and answer these three computational problems, noise, dynamism, and scale. However, people actively utilize social networking sites and diverse uses of these sites. The most common part of modern research analysis is instrumental for many social network analysis applications. There is an enormous quantity of data produced by users of social networks. Using Twitter, LinkedIn, Facebook, and other social media sites has become the most convenient way for people. Social network usage is growing exponentially in the most up-to-date decade though social networks are becoming increasingly popular every day, many users are continuously active social network users.

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