A User-Centric Feature Identification and Modeling Approach to Infer Social Ties in OSNs

Authors:
Mudassir Wani;Majed A. Alrubaian;Muhammad Abulaish
Affiliations:
Center of Excellence in Information Assurance, King Saud University Riyadh, Saudi Arabia;College of Computer and Information Science, King Saud University Riyadh, Saudi Arabia;Department of Computer Science, Jamia Millia Islamia, New Delhi-110025, India
Venue:
Proceedings of International Conference on Information Integration and Web-based Applications & Services
Year:
2013

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Abstract

This paper aims to identify user-centric features to calculate the strength of social ties between Online Social Network (OSN) users, and models the same using Latent Space Model (LSM). The modeling approach processes a socio-centric user-set as the users are directly (friend) or indirectly (friend-of-friend) related to a seed (target) user, which makes it easier to identify social ties between users as compared to random sampling from a set of diverse OSN users. For a given user, interaction data up to two levels is modeled and analyzed to generate a user-centric social network. Eleven different features related to Facebook have been identified to calculate the strength of social ties between users. LSM is used to visualize relationships in user-centric historical data and to estimate the probability of social ties between OSN users. The users are plotted using LSM in a three-dimensional (3D) social space around a seed user, and a link probability function is devised to calculate the probability of link between any two users with respect to the persona of the seed user. A sphere of influence around each user demarcating its active influence area is also identified and discussed in this paper.