Culture Based Preference for the Information Feeding Mechanism in Online Social Networks

Arunee RATIKAN  Mikifumi SHIKIDA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E97-D   No.4   pp.705-713
Publication Date: 2014/04/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E97.D.705
Type of Manuscript: Special Section PAPER (Special Section on Data Engineering and Information Management)
Category: 
Keyword: 
Online Social Networks,  information feeding mechanism,  information overload,  culture differences,  

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Summary: 
Online Social Networks (OSNs) have recently been playing an important role in communication. From the audience aspect, they enable audiences to get unlimited information via the information feeding mechanism (IFM), which is an important part of the OSNs. The audience relies on the quantity and quality of the information served by it. We found that existing IFMs can result in two problems: information overload and cultural ignorance. In this paper, we propose a new type of IFM that solves these problems. The advantage of our proposed IFM is that it can filter irrelevant information with consideration of audiences' culture by using the Naïve Bayes (NB) algorithm together with features and factors. It then dynamically serves interesting and important information based on the current situation and preference of the audience. This mechanism helps the audience to reduce the time spent in finding interesting information. It can be applied to other cultures, societies and businesses. In the near future, the audience will be provided with excellent, and less annoying, communication. Through our studies, we have found that our proposed IFM is most appropriate for Thai and some groups of Japanese audiences under the consideration of audiences' culture.