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

Arunee RATIKAN; Mikifumi SHIKIDA

doi:10.1587/transinf.E97.D.705

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

Arunee RATIKAN, Mikifumi SHIKIDA

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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.

Publication: IEICE TRANSACTIONS on Information Vol.E97-D No.4 pp.705-713

Publication Date: 2014/04/01

Publicized

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)

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Authors

Arunee RATIKAN
Japan Advanced Institute of Science and Technology (JAIST)
Mikifumi SHIKIDA
Japan Advanced Institute of Science and Technology (JAIST)

Keyword

Online Social Networks, information feeding mechanism, information overload, culture differences

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Arunee RATIKAN, Mikifumi SHIKIDA, "Culture Based Preference for the Information Feeding Mechanism in Online Social Networks" in IEICE TRANSACTIONS on Information, vol. E97-D, no. 4, pp. 705-713, April 2014, doi: 10.1587/transinf.E97.D.705.
Abstract: 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.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E97.D.705/_p

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@ARTICLE{e97-d_4_705,
author={Arunee RATIKAN, Mikifumi SHIKIDA, },
journal={IEICE TRANSACTIONS on Information},
title={Culture Based Preference for the Information Feeding Mechanism in Online Social Networks},
year={2014},
volume={E97-D},
number={4},
pages={705-713},
abstract={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.},
keywords={},
doi={10.1587/transinf.E97.D.705},
ISSN={1745-1361},
month={April},}

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TY - JOUR
TI - Culture Based Preference for the Information Feeding Mechanism in Online Social Networks
T2 - IEICE TRANSACTIONS on Information
SP - 705
EP - 713
AU - Arunee RATIKAN
AU - Mikifumi SHIKIDA
PY - 2014
DO - 10.1587/transinf.E97.D.705
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2014
AB - 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.
ER -