Big Data Analytics of Social Network Data: Who Cares Most About You on Facebook?

  • Carson K. LeungEmail author
  • Fan Jiang
  • Tik Wai Poon
  • Paul-Émile Crevier
Part of the Studies in Big Data book series (SBD, volume 27)


In recent years, many people are connected with each other via social networking sites such as Facebook, Google+, LinkedIn, Twitter, and Weibo. Many users on these social networking sites actively add posts or tweets so that they share their activities with their friends or connections. This leads to big social network data. For many of these creators of social network data (i.e., users on the social networking sites), it is not unusual for them to have hundreds or even thousands of friends or connections. Among these friends or connections, some of them care about the users by responding to the users’ posts or tweets (e.g., like these posts, add comments to the posts, or retweet the tweets) while some other are lurkers who just observe do not actively participate in any social network activities. How to distinguish those who care about you from those lurkers? To answer this question, we present in this book chapter big data management and analytics techniques on social network data. Specifically, our techniques help users discover friends or connections who cares most about them on social networking sites such as Facebook.


Social Network Data Primary Users Frequent Pattern Mining Association Rules Friendly Interaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This project is partially supported by Natural Sciences and Engineering Research Council of Canada (NSERC) and University of Manitoba.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Carson K. Leung
    • 1
    Email author
  • Fan Jiang
    • 1
  • Tik Wai Poon
    • 1
  • Paul-Émile Crevier
    • 1
  1. 1.University of ManitobaWinnipegCanada

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