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Predicting Links in Social Networks Using Text Mining and SNA

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3 Author(s)
Bartal, A. ; Ind. & Manage. Eng., Ben-Gurion Univ., Beer-Sheva, Israel ; Sasson, E. ; Ravid, G.

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 challenge. 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.

Published in:

Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in

Date of Conference:

20-22 July 2009