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Data Mining in On-Line Social Network for Marketing Response Analysis

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2 Author(s)
Surma, J. ; Fac. of Bus. Adm., Warsaw Sch. of Econ., Warsaw, Poland ; Furmanek, A.

Business usage of online social networks is a natural result of their intense development in last years. The information about members of a given community can be treated as a basis of correct identification of their needs and as a result adjusting personalized marketing messages. In this study, we will discuss the classification and regression trees (C&RT) model for identifying users of on-line social network likely to respond to a marketing campaign. This model is aimed at using the advanced data mining methods to enable business usage of social networks and related study problems concerning the importance of relational attributes in customer behavior analysis. The research presented in this paper confirms the usage of data mining techniques in marketing campaign optimization. This was justified by significant improvement in response rate. We also showed that extension of the user description by relational attributes did not improve the classical approach based on the individual attributes.

Published in:

Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 2011 IEEE Third International Conference on

Date of Conference:

9-11 Oct. 2011