Predicting links in social networks using text mining and SNA

Alon Bartal, Elan Sasson, Gilad Ravid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

Lately there is great progress in business organizations perception towards social aspects. Competitive organizations need to create innovation and segregate in the market. Business interactions help reaching those goals but finding the effective interactions is a chalange. We propose a prediction method, based on Social Networks Analysis (SNA) and text data mining (TDM), for predicting which nodes in a social network will be linked next. The network which is used to demonstrate the proposed prediction method is composed of academic co-authors who collaborated on writing articles. Without loss of generality, the academic co-authoring network demonstrates the proposed prediction procedure due to its similarity to other networks, such as business co-operation networks. The results show that the best prediction is achieved by incorporating TDM with SNA.

Original languageEnglish
Title of host publicationProceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009
Pages131-136
Number of pages6
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009 - Athens, Greece
Duration: 20 Jul 200922 Jul 2009

Publication series

NameProceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009

Conference

Conference2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009
Country/TerritoryGreece
CityAthens
Period20/07/0922/07/09

Keywords

  • Prediction social network analysis
  • Social network
  • Styling

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