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
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;
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
DOI :
10.1109/ASONAM.2010.21