Defining the Factors that Effect User Interest on Social Network News Feeds via Fuzzy Association Rule Mining: The Case of Sports News

Defining the Factors that Effect User Interest on Social Network News Feeds via Fuzzy Association Rule Mining: The Case of Sports News

Basar Öztaysi, Sezi Çevik Onar
Copyright: © 2013 |Pages: 12
DOI: 10.4018/978-1-4666-4213-3.ch015
OnDemand:
(Individual Chapters)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

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.
Chapter Preview
Top

Literature Review

In literature various studies focuses on the user interest on social media. These studies can be grouped in to three classes. The first group focuses on finding social media that suits user needs and classified the social media with this objective (Zhu et al., 2012; Kim et al., 2011; Denecke & Nejdl, 2009). Kim et al. (2011) focused on the problem of finding social media suited to user’s needs and proposed an approach for understanding user interests that can be exploited to recommender systems by using user-generated tags. Denecke and Nejdl (2009) classified blogs based on their information content via a content analysis.

Second group focuses on the user’s motivation and tried to reveal the motivation behind social media user interests (Sashittal et al., 2012; Men & Tsai, 2012; Alikilic & Atabek, 2012). Sashittal et al. (2012) claimed that the motivation behind Facebook usage makes Facebook users poor prospects for advertisers therefore if the advertisement investments on Facebook are not properly made they can be a waste. Ko (2012) tried to reveal the factors effecting continuous usage of social networking sites.

Complete Chapter List

Search this Book:
Reset