—The ability to influence individuals on online social networks for dissemination of information is crucial for commercial advertising, online marketing, political campaigning and, for the general public. However, there is still a research gap in understanding the underlying structure of these networks, their structural properties and how these properties can be leveraged in other research areas. Though information dissemination is a key objective of most online social networks, several influence models that are proposed in the literature are based on simulations, greedy and heuristic approaches, which sometimes are computationally expensive. Thus, these approaches do not take advantage of the underlying properties of these networks for effective and efficient information dissemination. This is because these network structural properties are not well-studied couples with the computationally expensive algorithms for implementing information diffusion on them. To this end, we propose to address these gaps in three folds. Firstly, the structural properties of several online social networks are studied to have a thorough overview of their underlying structure. Secondly, an efficient information diffusion algorithm is proposed and implemented with a less computational time that scales , where N is the number of nodes. Thirdly, we apply the algorithm to these networks and an influence index is calculated on them in order to study the impact of their structural properties on information diffusion and also as a way to characterize them. The results show that the networks structural properties of online social networks such as the average clustering coefficient, average degree, degree entropy, edge entropy among others, are effective in disseminating information as they correlate well with the influence index.
—Network structural properties, influence radius, information dissemination, online social networks.
The authors are with the School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China (e-mail: firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, email@example.com).
Cite:Edward Yellakuor Baagyere, Zhen Qin, Hu Xiong, and Qin Zhiguang, "Exploiting Online Social Network Structural Properties for Information Spreading," International Journal of Information and Electronics Engineering vol. 6, no. 4, pp. 247-255, 2016.