Affiliation:
1. Istanbul Technical University, Turkey
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.
Reference34 articles.
1. Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. In SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data (pp. 207-216).
2. Social media adoption among Turkish public relations professionals: A survey of practitioners
3. Data Mining in Social Media
4. Barbier, G., Tang, L., & Liu, H. (2011). Understanding online groups through social media. Wiley interdisciplinary reviews: Data mining and knowledge discovery archive, 1(4), 330-338.
5. Cai, X., Bain, M., Krzywicki, A., Wobcke, W., & Kim, Y. S. (2010). In P. Compton and A. Mahidadia (Eds.), Collaborative filtering for people to people recommendation in social networks. AI 2010: Advances in Artificial Intelligence Lecture Notes in Computer Science, 6464, 476-485.
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