Abstract
In recent development of computer technology, social networks are evolved as complex networks. Most challenging questions are to understand dynamics of user behavior on social network applications. In this paper, structural and dynamical modeling issues have been investigated. Social networks are treated as random graphs where a node is indicator variable of an entity on social network. The term random graph refers to the messy nature of the arrangement of links between different nodes. ER random graphs are generated by linking pair of randomly selected nodes. There are several characteristics of nodes to categorize them such as average path length, clustering coefficient to the each node. Nodes categorized with the help of self-organizing map algorithm and other statistical inference mechanism. Activities on social network are such as posting, commenting, sharing, and sending message, watch videos, and advertisements which are modeled as random events on random graphs.
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Kumar, H., Yadav, S.K. (2018). Relation Between Facebook Stories and Hours of a Day. In: Perez, G., Mishra, K., Tiwari, S., Trivedi, M. (eds) Networking Communication and Data Knowledge Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 4. Springer, Singapore. https://doi.org/10.1007/978-981-10-4600-1_10
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DOI: https://doi.org/10.1007/978-981-10-4600-1_10
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