Artificial Intelligence in Public Relations and Association Rule Mining as a Decision Support Tool

International Journal of Humanities and Social Science

© 2022 by SSRG - IJHSS Journal

Volume 9 Issue 3

Year of Publication : 2022

Authors : Kareem Mohamed, Ümmü Altan Bayraktar

10.14445/23942703/IJHSS-V9I3P105

How to Cite?

Kareem Mohamed, Ümmü Altan Bayraktar, "Artificial Intelligence in Public Relations and Association Rule Mining as a Decision Support Tool," SSRG International Journal of Humanities and Social Science, vol. 9,  no. 3, pp. 23-32, 2022. Crossref, https://doi.org/10.14445/23942703/IJHSS-V9I3P105

Abstract:

Association Rule Mining (ARM) is an important data mining technique for finding frequent terms that are very useful in evaluating and recommending a range of activities a business will implement to entice customers. This study aims to highlight the importance of ARM and to shed light on Public Relations (PR) practitioners to increase the effectiveness of data mining tools such as WEKA. Rather than providing a comprehensive description of the algorithm used, the analysis included in the study paints a general picture of how this technique can be used to facilitate PR practices. In this framework, filtering, processing, and term calculations on the collected data were made using WEKA. Analysis and understanding of output rules are one of the main tasks that Public Relations practitioners must perform. In summary, it is concluded that ARM can be used effectively in PR applications such as cross-selling, targeted campaigns, and managing activities.

Keywords:

Artificial Intelligence, Association rule mining, Data mining, Weka, Public relations.

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