research-article

An empirical analysis of characteristics of useful comments in social media

Authors:

Elaheh Momeni,

Gerhard SagederAuthors Info & Claims

WebSci '13: Proceedings of the 5th Annual ACM Web Science Conference

Pages 258 - 261

https://doi.org/10.1145/2464464.2464490

Published: 02 May 2013 Publication History

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Abstract

User-generated comments in online social media have recently attracted increasing attention with regard to the integration of end users' knowledge with the creation of new descriptive annotations for media resources (such as exploiting a comment written on a Flickr photo in order to create descriptive annotations for the photo). However, users have different levels of expertise and the content quality of comments varies from useful to useless. In this paper, we compare the characteristics of useful comments on different platforms (YouTube and Flickr) and we propose a method for inferring useful comments. We provide an analysis of the impact of different textual, semantic, and user features on the proposed inference method.

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He CHe LLu TLi B(2021)Beyond Entertainment: Unpacking Danmaku and Comments' Role of Information Sharing and Sentiment Expression in Online Crisis VideosProceedings of the ACM on Human-Computer Interaction10.1145/34795555:CSCW2(1-27)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3479555
Choi SSegev A(2019)Finding Informative Comments for Video ViewingSN Computer Science10.1007/s42979-019-0048-21:1Online publication date: 21-Nov-2019
https://doi.org/10.1007/s42979-019-0048-2
Zhong JXiong YGuo WXie J(2016)EDAHT: An Expertise Degree Analysis Model for Mass Comments in the E-Commerce SystemAdvanced Data Mining and Applications10.1007/978-3-319-49586-6_32(472-480)Online publication date: 13-Nov-2016
https://doi.org/10.1007/978-3-319-49586-6_32
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An empirical analysis of characteristics of useful comments in social media
1. Information systems
  1. Information retrieval
  2. Information storage systems

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Published In

WebSci '13: Proceedings of the 5th Annual ACM Web Science Conference

May 2013

481 pages

ISBN:9781450318891

DOI:10.1145/2464464

Conference Chairs:
Hugh Davis
University of Southampton
,
Harry Halpin
World Wide Web Consortium
,
Alex Pentland,
Program Chairs:
Mark Bernstein,
Lada Adamic,
Harith Alani,
Alexandre Monnin,
Richard Rogers

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 02 May 2013

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WebSci '13: Web Science 2013

May 2 - 4, 2013

Paris, France

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Overall Acceptance Rate 245 of 933 submissions, 26%

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He CHe LLu TLi B(2021)Beyond Entertainment: Unpacking Danmaku and Comments' Role of Information Sharing and Sentiment Expression in Online Crisis VideosProceedings of the ACM on Human-Computer Interaction10.1145/34795555:CSCW2(1-27)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3479555
Choi SSegev A(2019)Finding Informative Comments for Video ViewingSN Computer Science10.1007/s42979-019-0048-21:1Online publication date: 21-Nov-2019
https://doi.org/10.1007/s42979-019-0048-2
Zhong JXiong YGuo WXie J(2016)EDAHT: An Expertise Degree Analysis Model for Mass Comments in the E-Commerce SystemAdvanced Data Mining and Applications10.1007/978-3-319-49586-6_32(472-480)Online publication date: 13-Nov-2016
https://doi.org/10.1007/978-3-319-49586-6_32
Vasconcelos MAlmeida JGonçalves MCho YShin SKim SHung CHong J(2014)What makes your opinion popular?Proceedings of the 29th Annual ACM Symposium on Applied Computing10.1145/2554850.2554911(598-603)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2554850.2554911

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How useful are your comments?: analyzing and predicting youtube comments and comment ratings

Identification of useful user comments in social media: a case study on flickr commons

Sentiment Analysis Using Word Polarity of Social Media

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