Application of Datamining Technique in Social Networking Sites: Facebook as a Case

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Karuna C. Gull
Dr. Santosh kumar Gandhi, Santoshkumar B. Shali


Currently, social networks such as Facebook or Twitter are getting more and more popular due to the opportunities they offer. As of
November 2009, Facebook was the most popular and well known social network throughout the world with over 316 million users. Among the
countries, Turkey is in third place in terms of Facebook users and half of them are younger than 25 years old (students). Turkey has 14 million
Facebook members. The success of Facebook and the rich opportunities offered by social media sites lead to the creation of new web based
applications for social networks and open up new frontiers. Thus, discovering the usage patterns of social media sites might be useful in taking
decisions about the design and implementation of those applications as well as educational tools. Therefore, in this study, the factors affecting
“Facebook usage time†and â€Facebook access frequency†are revealed via various predictive data mining techniques, based on a questionnaire
applied on 570 Facebook users. At the same time, the associations of the students’ opinions on the contribution of Facebook in an educational aspect
are investigated by employing the association rules method.

Keywords: Artificial neural networks (ANN), Association rules, Decision trees, Facebook, Social networks, Support Vector Machine (SVM ).


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