Predicting Facebook Group Relationship
Poonam Rani1, M.P.S. Bhatia2, Devendra K. Tayal3

1Poonam Rani*, Division of Computer Engineering, NSUT, Dwarka, India.
2M.P.S. Bhatia, Division of Computer Engineering, NSUT, Dwarka, India.
3Devendra. K. Tayal, Computer Engineering, IGDTUW University, Delhi, India. 

Manuscript received on 25 August 2019. | Revised Manuscript received on 03 September 2019. | Manuscript published on 30 September 2019. | PP: 1862-1869 | Volume-8 Issue-11, September 2019. | Retrieval Number: K18040981119/2019©BEIESP | DOI: 10.35940/ijitee.K1804.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Facebook has become the leading social networking site in most countries worldwide. It provides a diverse platform that caters to social, educational and entertainment needs of a user. So, this paper has focused on the Sociocentric Analysis of Facebook. It predicts group relationship of the Facebook social network. The paper proposes to aggregate user’s relationships with similar interests and perspectives on the basis of the way in which they provide a reaction to a post on Facebook. The paper has selected the widely used reactions on Facebook posts. The selected reactions on posts are Like, Laugh, Sad, and Wow. In this, a fuzzy pairwise relation between two users in the social network is obtained. For every pair of social actors or users, we have extracted the total number of Facebook posts to which they have reacted in a particular way over a fortnight. The number for each reaction is multiplied with the corresponding weight of the reaction computed by Analytics Hierarchy Process. This fuzzy pairwise relationship is further employed for finding the closely linked group between users by using Ordered Weighted Averaging operator. The devised algorithm has been applied to a sample data of students connected via Facebook social network. The paper has also given several application areas for the proposed work.
Keywords: Social networks, social network analysis, Fuzzy logic, Fuzzy quantifiers, Analytics Hierarchy Process (AHP), Ordered Weighted Averaging (OWA) operator.
Scope of the Article: