DocumentCode
1918226
Title
Improving Marketing Response by Data Mining in Social Network
Author
Surma, Jerzy ; Furmanek, Anna
Author_Institution
Coll. of Bus. Adm., Warsaw Sch. of Econ., Warsaw, Poland
fYear
2010
fDate
9-11 Aug. 2010
Firstpage
446
Lastpage
451
Abstract
Social networks have generated great expectations connected with their potential business value. The purpose of our research is to present that even a rudimentary application of data mining techniques can bring statistically significant improvement in marketing response accuracy throughout the virtual community. In our test the C&RT (classification and regression tree) approach was used to generate a classification tree that allows us to formulate some specific rules to identify the proper target group. In the performed empirical experiments, based on the real social network data, we showed that it is possible to improve marketing response. This promising result was obtained without any advanced and time consuming transformation of the available data.
Keywords
Internet; data mining; marketing data processing; regression analysis; social networking (online); tree data structures; classification and regression tree; data mining; marketing response improvement; social network; virtual community; Biological system modeling; Business; Classification tree analysis; Data mining; Data models; Predictive models; Social network services; classification tree; data mining; marketing response; social network;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on
Conference_Location
Odense
Print_ISBN
978-1-4244-7787-6
Electronic_ISBN
978-0-7695-4138-9
Type
conf
DOI
10.1109/ASONAM.2010.21
Filename
5563062
Link To Document