Abstract
Memes have taken the center stage as far as present day social media network is concerned. Every second, about a million memes are shared on various social media. In this paper we analyze a dataset which consist of data related to meme sharing and corresponding phrases used in the process. Popularity of memes is tracked followed by timestamps to identify the most shared memes across the internet. Meme sharing or propagation is also based on some hidden patterns like a social incident, a soccer game, a war or speeches by a public figures. The paper aims to produce a multivariate graph with the source of memes as nodes which are connected to other sources sharing the same meme using edges. The graph is then analyzed to identify patterns and genre of popular memes.
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Pandey, A., Mukherjee, S., Bajaj, S., Jonnalagadda, A. (2019). Identification of Meme Genre and Its Social Impact. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 105. Springer, Singapore. https://doi.org/10.1007/978-981-13-1927-3_2
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DOI: https://doi.org/10.1007/978-981-13-1927-3_2
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