Big data in online social networks: User interaction analysis to model user behavior in social networks

Divyakant Agrawal, Ceren Budak, Amr El Abbadi, Theodore Georgiou, Xifeng Yan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Citations (Scopus)

Abstract

With hundreds of millions of users worldwide, social networks provide incredible opportunities for social connection, learning, political and social change, and individual entertainment and enhancement in a multiple contexts. Because many social interactions currently take place in online networks, social scientists have access to unprecedented amounts of information about social interaction. Prior to the advent of such online networks, these investigations required resource-intensive activities such as random trials, surveys, and manual data collection to gather even small data sets. Now, massive amounts of information about social networks and social interactions are recorded. This wealth of big data can allow social scientists to study social interactions on a scale and at a level of detail that has never before been possible. Our goal is to evaluate the value of big data in various social applications and build a framework that models the cost/utility of data. By considering important problems such as Trend Analysis, Opinion Change and User Behavior Analysis during major events in online social networks, we demonstrate the significance of this problem. Furthermore, in each case we present scalable techniques and algorithms that can be used in an online manner. Finally, we propose the big data value evaluation framework that weighs in the cost as well as the value of data to determine capacity modeling in the context of data acquisition.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages1-16
Number of pages16
Volume8381 LNCS
DOIs
Publication statusPublished - 14 Apr 2014
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8381 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

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Keywords

  • Big Data
  • Complex Networks
  • Data Streams
  • Social Analytics
  • Social Networks

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Agrawal, D., Budak, C., El Abbadi, A., Georgiou, T., & Yan, X. (2014). Big data in online social networks: User interaction analysis to model user behavior in social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8381 LNCS, pp. 1-16). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8381 LNCS). https://doi.org/10.1007/978-3-319-05693-7_1