A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs

Wayne Xin Zhao; Jing Liu; Yulan He; Chin Yew Lin; Ji-Rong Wen

doi:10.1109/ASONAM.2014.6921626

A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs

Wayne Xin Zhao, Jing Liu, Yulan He, Chin Yew Lin, Ji-Rong Wen

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally 'Sina microblogging'). We found that there is a strong correlation between expertise levels and social media influence scores. In addition, different expertise levels showed influence variation patterns: high-expertise celebrities have stronger influence on the 'audience' in their expertise domains.

Original language	English
Title of host publication	Proceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining
Subtitle of host publication	ASONAM 2014
Editors	Xindong Wu, Martin Ester, Guandong Xu
Place of Publication	Piscataway, NJ (US)
Publisher	IEEE
Pages	460-463
Number of pages	4
ISBN (Print)	978-1-4799-5877-1, 978-1-4799-5876-4
DOIs	https://doi.org/10.1109/ASONAM.2014.6921626
Publication status	Published - 31 Dec 2014
Event	2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining - Beijing, China Duration: 17 Aug 2014 → 20 Aug 2014

Conference

Conference	2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining
Abbreviated title	ASONAM 2014
Country/Territory	China
City	Beijing
Period	17/08/14 → 20/08/14

Bibliographical note

Funding: EPSRC grant EP/L010690/1

Keywords

expertise
microblog
social media influence

Access to Document

10.1109/ASONAM.2014.6921626

Cite this

Zhao, W. X., Liu, J., He, Y., Lin, C. Y., & Wen, J-R. (2014). A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs. In X. Wu, M. Ester, & G. Xu (Eds.), Proceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining: ASONAM 2014 (pp. 460-463). IEEE. https://doi.org/10.1109/ASONAM.2014.6921626

Zhao, Wayne Xin ; Liu, Jing ; He, Yulan et al. / A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs. Proceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining: ASONAM 2014. editor / Xindong Wu ; Martin Ester ; Guandong Xu. Piscataway, NJ (US) : IEEE, 2014. pp. 460-463

@inproceedings{03f1d32d79ca4babb2b824d1e356fd9e,

title = "A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs",

abstract = "Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally 'Sina microblogging'). We found that there is a strong correlation between expertise levels and social media influence scores. In addition, different expertise levels showed influence variation patterns: high-expertise celebrities have stronger influence on the 'audience' in their expertise domains.",

keywords = "expertise, microblog, social media influence",

author = "Zhao, {Wayne Xin} and Jing Liu and Yulan He and Lin, {Chin Yew} and Ji-Rong Wen",

note = "Funding: EPSRC grant EP/L010690/1; 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining, ASONAM 2014 ; Conference date: 17-08-2014 Through 20-08-2014",

year = "2014",

month = dec,

day = "31",

doi = "10.1109/ASONAM.2014.6921626",

language = "English",

isbn = "978-1-4799-5877-1",

pages = "460--463",

editor = "Xindong Wu and Martin Ester and Guandong Xu",

booktitle = "Proceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining",

publisher = "IEEE",

address = "United States",

}

Zhao, WX, Liu, J, He, Y, Lin, CY & Wen, J-R 2014, A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs. in X Wu, M Ester & G Xu (eds), Proceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining: ASONAM 2014. IEEE, Piscataway, NJ (US), pp. 460-463, 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining, Beijing, China, 17/08/14. https://doi.org/10.1109/ASONAM.2014.6921626

A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs. / Zhao, Wayne Xin; Liu, Jing; He, Yulan et al.
Proceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining: ASONAM 2014. ed. / Xindong Wu; Martin Ester; Guandong Xu. Piscataway, NJ (US): IEEE, 2014. p. 460-463.

Research output: Chapter in Book/Published conference output › Conference publication

TY - GEN

T1 - A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs

AU - Zhao, Wayne Xin

AU - Liu, Jing

AU - He, Yulan

AU - Lin, Chin Yew

AU - Wen, Ji-Rong

N1 - Funding: EPSRC grant EP/L010690/1

PY - 2014/12/31

Y1 - 2014/12/31

N2 - Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally 'Sina microblogging'). We found that there is a strong correlation between expertise levels and social media influence scores. In addition, different expertise levels showed influence variation patterns: high-expertise celebrities have stronger influence on the 'audience' in their expertise domains.

AB - Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally 'Sina microblogging'). We found that there is a strong correlation between expertise levels and social media influence scores. In addition, different expertise levels showed influence variation patterns: high-expertise celebrities have stronger influence on the 'audience' in their expertise domains.

KW - expertise

KW - microblog

KW - social media influence

UR - http://www.scopus.com/inward/record.url?scp=84911096356&partnerID=8YFLogxK

U2 - 10.1109/ASONAM.2014.6921626

DO - 10.1109/ASONAM.2014.6921626

M3 - Conference publication

AN - SCOPUS:84911096356

SN - 978-1-4799-5877-1

SN - 978-1-4799-5876-4

SP - 460

EP - 463

BT - Proceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining

A2 - Wu, Xindong

A2 - Ester, Martin

A2 - Xu, Guandong

PB - IEEE

CY - Piscataway, NJ (US)

T2 - 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining

Y2 - 17 August 2014 through 20 August 2014

ER -

Zhao WX, Liu J, He Y, Lin CY, Wen J-R. A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs. In Wu X, Ester M, Xu G, editors, Proceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining: ASONAM 2014. Piscataway, NJ (US): IEEE. 2014. p. 460-463 doi: 10.1109/ASONAM.2014.6921626

A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs

Abstract

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this