Patterns affecting structural properties of social networking site 'Twitter' Online publication date: Fri, 09-Mar-2018
by Vinay Singh; Anurag Singh; Divya Jain; Vimal Kumar; Pratima Verma
International Journal of Business Information Systems (IJBIS), Vol. 27, No. 4, 2018
Abstract: Online social networking platforms are kind of complex networks where users are treated as nodes for interactions among them. Understanding such complex network is critical to enhance their existing frameworks and important to incorporate new future applications. Thus, a mixing network pattern is possible due to the diversified geographic locations on user. The present study is focused on measuring assortativity coefficient of network complexity and its effect on the structural properties of the network. We examined crawled users data (group wise) gathered from 'Twitter' by using open source API. Among the group, all the users are ranked according to their followers count. As part of algorithmic process, the assortativity coefficient is calculated in various steps by removing few nodes randomly from the existing network group. It is found that network is resilient to the deletion of highest degree nodes and assortativity is indeed present in network.
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