Abstract
The tremendous use of internet, mobile platforms, online commerce sites, social media services, human behavior is very easily recorded in digital world. From these information various facts can be observed, like, in which discussion in online social network we participate, with whom we communicate the most, how we download or buy something from online e-commerce sites, are we influenced by certain classes of people etc. The major crux in all these activities are sharing of information and its diffusion. The study of the information diffusion has become a challenging proposition for the research fraternity. Some of these discussions sometimes becomes more popular and is called as meme. Modern research trends also show study of content popularity of these memes. The proposition becomes more challenging due to the fact that the information changes in real-time in the online social networks and the data generated is very huge or big data. In this paper a study is made to analyse how a piece of information spreads over the internet, and how some topics get very popular while others fade away. The approach in the paper begins with social network analysis (SNA) of the data to analyze and investigate underlying social structure. Then this information is used to detect most frequently used phrases and quotes or memes that becomes more popular across any communications over time. The results of the work are reported and compared with some recent study. The efficacy of the work is more evident as the approach is studied in not only standard data set but also in real time data.
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Maji, B., Bhattacharya, I., Nag, K., Mishra, U.P., Dasgupta, K. (2019). Study of Information Diffusion and Content Popularity in Memes. In: Mandal, J., Mukhopadhyay, S., Dutta, P., Dasgupta, K. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2018. Communications in Computer and Information Science, vol 1031. Springer, Singapore. https://doi.org/10.1007/978-981-13-8581-0_37
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