DocumentCode
2775368
Title
Data Mining in On-Line Social Network for Marketing Response Analysis
Author
Surma, Jerzy ; Furmanek, Anna
Author_Institution
Fac. of Bus. Adm., Warsaw Sch. of Econ., Warsaw, Poland
fYear
2011
fDate
9-11 Oct. 2011
Firstpage
537
Lastpage
540
Abstract
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.
Keywords
Internet; classification; consumer behaviour; data mining; marketing data processing; social networking (online); trees (mathematics); C&RT model; business usage; classification and regression trees; customer behavior analysis; data mining; marketing campaign; marketing response analysis; online social network; personalized marketing message; Analytical models; Business; Communities; Data mining; Educational institutions; Predictive models; Social network services; On-line social networks analysis; data mining; marketing response analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 2011 IEEE Third International Conference on
Conference_Location
Boston, MA
Print_ISBN
978-1-4577-1931-8
Type
conf
DOI
10.1109/PASSAT/SocialCom.2011.72
Filename
6113163
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