Affiliation:
1. Department of Computer Science and Engineering (DCSE), Thapar Institute of Engineering and Technology, Patiala, Patiala, India
2. School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India
3. Department of Artificial Intelligence & Machine Learning, Manipal University, Jaipur, Jaipur, India
Abstract
Due to the explosive rise of online social networks, social network analysis (SNA) has emerged as a significant academic field in recent years. Understanding and examining social relationships in networks through network analysis opens up numerous research avenues in sociology, literature, media, biology, computer science, sports, and more. Therefore, certain studies review and discuss some research verticals of SNA, such as viral marketing, information diffusion, clustering, link prediction, and so on, to provide background knowledge and understanding. These studies still lack the SNA process, tools, and practical aspects in multidisciplinary applications. Inspired by these facts, we have discussed the background, process, tools, and application of SNA. First, we have presented a detailed description of the SNA process. Thereafter, we presented a comparative analysis of SNA tools and languages. Finally, we have discussed the various applications corresponding to SNA research verticals.
Publisher
Association for Computing Machinery (ACM)
Cited by
2 articles.
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