Chen, L;
Büscher, M;
Hu, Y;
(2020)
Crowding out the crowd: The transformation of network disaster communication patterns on Weibo.
In: Hughes, Amanda Lee and McNeill, Fiona and Christopher, Zobel, (eds.)
Proceedings of the 17th ISCRAM Conference.
(pp. pp. 472-489).
Information Systems for Crisis Response and Management (ISCRAM): Blacksburg, VA, USA.
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Abstract
There is a surge in people turning to social media in disasters in China. In the 2010 Yushu earthquake, 5,979 Weibos were posted. Almost 10 years on, in the 2019 Yibin earthquake it was 17,495. This study presents a Social Network Analysis of the dynamics of this growth, taking the six major Chinese earthquakes of this decade as a case study. By constructing relationship matrices, the research reveals a transformation of networked crisis communication patterns on Weibo. We show how communication relationships between verified organisational users, government agencies, verified individual users (such as celebrities) and unverified ordinary users have changed, and we observe that government agencies are ‘crowding out the crowd’ of other users. We consider key aspects and the ethical complexities of this phenomenon.
Type: | Proceedings paper |
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Title: | Crowding out the crowd: The transformation of network disaster communication patterns on Weibo |
Event: | 17th ISCRAM Conference |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | https://ojs.iscram.org/index.php/Proceedings/about |
Language: | English |
Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Weibo, transformation, crowding out, crisis communication, mobilities |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute |
URI: | https://discovery.ucl.ac.uk/id/eprint/10210770 |
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