Proposal of a Ranking Method for Comments in Social Media Using Ratings of Comment Posters

Keiichi Endo

Proposal of a Ranking Method for Comments in Social Media Using Ratings of Comment Posters

Keiichi Endo * §

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Ehime University

Proposal of a Ranking Method for Comments in Social Media Using Ratings of Comment Posters

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Abstract

Many social media adopt a ranking method in which comments are ranked in the order of the number of ratings attached to each comment. However, this method has the disadvantage of ratings being concentrated on comments posted at an early stage. Even if there are high-quality comments posted later, most of them are buried without being noticed. This paper proposes a ranking method that considers not only the ratings for each comment but also the previous ratings the comment poster has received. The effectiveness of the proposed method is evaluated through a simulation. We demonstrate that with the proposed method, high-quality comments are displayed in the higher positions regardless of the posting period.

References

12 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Keiichi Endo. 2013. "Proposal of a Ranking Method for Comments in Social Media Using Ratings of Comment Posters". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 13 (GJCST Volume 13 Issue G3).

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GJCST Volume 13 Issue G3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

comment comment poster ranking method rating social-media

Classification

GJCST-G Classification J.4

Submission ReceivedDecember 16, 2012
Peer Review Double Blind
Handling Editor
Accepted January 3, 2013
Published January 15, 2013

Version of record

v1.2

Issue date

September 28, 2013

Language

English

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Article Matrices

Total Score: 189

Country: Japan

Subject: Global Journal of Computer Science and Technology

Authors: Keiichi Endo, Hiroshi Fujita, Dai Okano, Kaname Amano (PhD/Dr. count: 0)

View Count (all-time): 542

Total Views (Real + Logic): 3897

Total Downloads (simulated): 233

Publish Date: 2013 01, Tue

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Total Views: 3.9K

Total Downloads: 233

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