Identification of User Patterns in Social Networks by Data Mining Techniques: Facebook Case

  • A. Selman Bozkır
  • S. Güzin Mazman
  • Ebru Akçapınar Sezer
Part of the Communications in Computer and Information Science book series (CCIS, volume 96)


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 ”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.


Social networks decision trees Facebook association rules 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • A. Selman Bozkır
    • 1
  • S. Güzin Mazman
    • 2
  • Ebru Akçapınar Sezer
    • 1
  1. 1.Department of Computer EngineeringHacettepe UniversityAnkaraTurkey
  2. 2.Department of Computer Education and Instructional TechnologiesHacettepe UniversityAnkaraTurkey

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