Defining the factors that effect user interest on social network news feeds via fuzzy association rule mining: The case of sports news

Başar Öztayşi*, Sezi Çevik Onar

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)

Abstract

Social networking became one of the main marketing tools in the recent years since it's a faster and cheaper way to reach the customers. Companies can use social networks for efficient communication with their current and potential customers but the value created through the usage of social networks depends on how well the organizations use these tools. Therefore a support system which will enhance the usage of these tools is necessary. Fuzzy Association rule mining (FARM) is a commonly used data mining technique which focuses on discovering the frequent items and association rules in a data set and can be a powerful tool for enhancing the usage of social networks. Therefore the aim of the chapter is to propose a fuzzy association rule mining based methodology which will present the potential of using the FARM techniques in the field of social network analysis. In order to reveal the applicability, an experimental evaluation of the proposed methodology in a sports portal will be presented.

Original languageEnglish
Title of host publicationData Mining in Dynamic Social Networks and Fuzzy Systems
PublisherIGI Global
Pages334-345
Number of pages12
ISBN (Electronic)9781466642140
ISBN (Print)9781466642133
DOIs
Publication statusPublished - 30 Jun 2013

Bibliographical note

Publisher Copyright:
© 2013 by IGI Global. All rights reserved.

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