Authors: Vinay Singh; Anurag Singh; Divya Jain; Vimal Kumar; Pratima Verma
Addresses: ABV Indian Institute of Information Technology and Management, Gwalior, MP 474010, India ' Department of Computer Science and Engineering, National Institute of Technology Delhi, Delhi 110040, India ' ABV Indian Institute of Information Technology and Management, Gwalior, MP 474010, India ' Department of Industrial and Management Engineering, Indian Institute of Technology, Kanpur, UP 208016, India ' Department of Industrial and Management Engineering, Indian Institute of Technology, Kanpur, UP 208016, India
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.
Keywords: mixing patterns; assortativity coefficient; robustness; dynamics of a network; homophily.
International Journal of Business Information Systems, 2018 Vol.27 No.4, pp.411 - 432
Received: 21 Mar 2016
Accepted: 02 Sep 2016
Published online: 09 Mar 2018 *