Abstract
In recent few years, due to the exponential growth of users on online social networking sites (OSNs), mainly over micro-blogging sites like Twitter, the OSNs now resemble the real world very cohesively. The excess of continuously user-generated online textual data by OSNs that encapsulates almost all verticals of the real world has attracted many researchers who are working in the area of text mining, natural language processing (NLP), machine learning, and data mining. This paper discusses the feasibility of OSNs in detecting real-world events from the horizon of the virtual world formed over OSNs. Moreover, this paper also describes the framework for real-world event detection through online social networking sites.
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Srivastava, R., Bhatia, M.P.S., Tayal, V., Verma, J.K. (2019). Framework for Real-World Event Detection Through Online Social Networking Sites. In: Jain, L., E. Balas, V., Johri, P. (eds) Data and Communication Networks. Advances in Intelligent Systems and Computing, vol 847. Springer, Singapore. https://doi.org/10.1007/978-981-13-2254-9_17
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DOI: https://doi.org/10.1007/978-981-13-2254-9_17
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