short-paper

How "big vs" dominate chinese microblog: a comparison of verified and unverified users on sina weibo

Authors:

Ning Wang,

James She,

Junting ChenAuthors Info & Claims

WebSci '14: Proceedings of the 2014 ACM conference on Web science

Pages 182 - 186

https://doi.org/10.1145/2615569.2615683

Published: 23 June 2014 Publication History

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Abstract

Sina Weibo has become the most popular microblogging platform in the Chinese-speaking community. Verification scheme is a distinctive element of Weibo with an aim to help the public to identify genuine accounts and select trustworthy information sources. Verified users are also known as "Big Vs", who are identified by a verification badge, a capitalised letter "V" added alongside account name. By comparing statistical characteristics of both verified and unverified users, this paper presents that a minority of verified users are largely consider as influentials, who tend to be more central in the networks and play vital roles in keeping connectivity as well as network robustness. Although the verification scheme is likely to draw more users to become influentials, user behaviours are still considerably more influenced by user roles rather than by verification scheme.

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https://doi.org/10.3390/e24050664
Liu XZhao JLiu RLiu K(2022)Event history analysis of the duration of online public opinions regarding major health emergenciesFrontiers in Psychology10.3389/fpsyg.2022.95455913Online publication date: 13-Sep-2022
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How "big vs" dominate chinese microblog: a comparison of verified and unverified users on sina weibo
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Published In

WebSci '14: Proceedings of the 2014 ACM conference on Web science

June 2014

318 pages

ISBN:9781450326223

DOI:10.1145/2615569

General Chairs:
Filippo Menczer
Indiana University, USA
,
Jim Hendler
Rensselaer Polytechnic Institute, USA
,
William Dutton
University of Oxford, UK
,
Program Chairs:
Markus Strohmaier
GESIS & University of Koblenz-Landau, Germany
,
Eric T. Meyer
University of Oxford, UK
,
Ciro Cattuto
ISI Foundation, Italy

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Published: 23 June 2014

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WebSci '14 Paper Acceptance Rate 29 of 144 submissions, 20%;

Overall Acceptance Rate 245 of 933 submissions, 26%

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https://doi.org/10.3390/e24050664
Liu XZhao JLiu RLiu K(2022)Event history analysis of the duration of online public opinions regarding major health emergenciesFrontiers in Psychology10.3389/fpsyg.2022.95455913Online publication date: 13-Sep-2022
https://doi.org/10.3389/fpsyg.2022.954559
Zheng QGuo YWang ZAndrasik FKuang ZLi JXu SHu X(2022)Exploring Weibo users’ attitudes toward lesbians and gays in Mainland ChinaComputers in Human Behavior10.1016/j.chb.2021.107021127:COnline publication date: 9-Apr-2022
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Tweeting under pressure: analyzing trending topics and evolving word choice on sina weibo

Automatic detection of rumor on Sina Weibo

A short-term trend prediction model of topic over Sina Weibo dataset

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