Title: Mining gender affinity to social networking

Authors: Phani Sajja; Rozita Jamili Oskouei

Addresses: Expert Software Consultants Ltd., B-77-78, 2nd Floor, Sindhuja Building, Sector – 6, NOIDA, UP, 201 301, India ' Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology, Allahabad, UP, 21004, India

Abstract: Social networking websites are currently used by many people, especially young ones who are in the age group of 17-25. Since these age groups are mostly students and are either college going or in the process of making a career, it is difficult for the parents to keep a close watch over their activities. Even the academic coordinators and advisors have not developed a pattern through which these age groups can be guided and trained. Nevertheless, it is difficult to pattern the personal and social behaviour, academic activities and performances. There is no exhaustive study or research work done to address this issue in different countries. In this research, a comprehensive analysis of students' internet usage behaviours by focusing on social network (SN) website usages is targeted. It is an attempt to pattern the characteristics by demonstrating and elaborating the various aspects of internet usages. Relationship between users' usage patterns and their personal and social behaviours along with their academic performances are studied, finally a prediction method for predicting students' future academic performance by analysing their internet and SN websites usage patterns is proposed.

Keywords: behaviour mining; internet usage patterns; social networking; social networks; web usage mining; WUM; website classification; gender affinity; student behaviour; students; data mining; personal behaviour; social behaviour; academic performance; usage monitoring; web mining.

DOI: 10.1504/IJSNM.2012.051056

International Journal of Social Network Mining, 2012 Vol.1 No.2, pp.160 - 184

Received: 07 May 2011
Accepted: 13 Mar 2012

Published online: 21 Aug 2014 *

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