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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationProceedings of the 2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining
Subtitle of host publicationASONAM 2014
EditorsXindong Wu, Martin Ester, Guandong Xu
Place of PublicationPiscataway, NJ (US)
PublisherIEEE
Pages460-463
Number of pages4
ISBN (Print)978-1-4799-5877-1, 978-1-4799-5876-4
DOIs
Publication statusPublished - 31 Dec 2014
Event2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining - Beijing, China
Duration: 17 Aug 201420 Aug 2014

Conference

Conference2014 IEEE/ACM international conference on Advances in Social Networks Analysis and Mining
Abbreviated titleASONAM 2014
CountryChina
CityBeijing
Period17/08/1420/08/14

Bibliographical note

Funding: EPSRC grant EP/L010690/1

Keywords

  • expertise
  • microblog
  • social media influence

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). Piscataway, NJ (US): IEEE. https://doi.org/10.1109/ASONAM.2014.6921626
Zhao, Wayne Xin ; Liu, Jing ; He, Yulan ; Lin, Chin Yew ; Wen, Ji-Rong. / 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",
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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; Lin, Chin Yew; Wen, Ji-Rong.

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/Report/Conference proceedingConference contribution

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.

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

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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 https://doi.org/10.1109/ASONAM.2014.6921626