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Social Network Analysis: A Survey on Measure, Structure, Language Information Analysis, Privacy, and Applications

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Abstract

The rapid growth in popularity of online social networks provides new opportunities in computer science, sociology, math, information studies, biology, business, and more. Social network analysis (SNA) is a paramount technique supporting understanding social relationships and networks. Accordingly, certain studies and reviews have been presented focusing on information dissemination, influence analysis, link prediction, and more. However, the ultimate aim is for social network background knowledge and analysis to solve real-world social network problems. SNA still has several research challenges in this context, including users’ privacy in online social networks. Inspired by these facts, we have presented a survey on social network analysis techniques, visualization, structure, privacy, and applications. This detailed study has started with the basics of network representation, structure, and measures. Our primary focus is on SNA applications with state-of-the-art techniques. We further provide a comparative analysis of recent developments on SNA problems in the sequel. The privacy preservation with SNA is also surveyed. In the end, research challenges and future directions are discussed to suggest to researchers a starting point for their research.

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          cover image ACM Transactions on Asian and Low-Resource Language Information Processing
          ACM Transactions on Asian and Low-Resource Language Information Processing  Volume 22, Issue 5
          May 2023
          653 pages
          ISSN:2375-4699
          EISSN:2375-4702
          DOI:10.1145/3596451
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          • Published: 9 May 2023
          • Online AM: 8 June 2022
          • Accepted: 25 May 2022
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          • Received: 31 December 2021
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