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Construction safety knowledge sharing on Twitter: A social network analysis

  • Qi Yao
    ,
  • Rita Yi Man Li
    ,
  • Lingxi Song
    ,
  • M. James C. Crabbe
  • Chongqing Technology and Business University
    ,
  • Hong Kong Shue Yan University
    ,
  • Rajamangala University of Technology Tawan-ok
    ,
  • University of Oxford
    ,
  • Shanxi University
Research Output: Contribution to journal Article Peer-review

Open access

Abstract

Many studies show that unsafe behavior is the main cause of construction accidents. Safety education and training are effective means to minimise people’s unsafe behaviors. Apart from traditional face-to-face construction knowledge sharing, social media is a good tool because it is convenient, efficient, and widely used. We applied both social network analysis and sentiment analysis to investigate knowledge sharing on Twitter. Our study is a novel attempt to understand social structure of “construction safety”- related twitter networks and the opinion leaders. We selected and analyzed 6561 tweets of three users’ networks on Twitter – “construction safety”, “construction health” and “construction accident”. We found that three networks had low density and many isolated vertices, which showed that users did not actively interact with each other. The opinion leaders in this study were mostly organizations or government agencies. The top one is “cif_ireland”, the Irish construction industry’s representative body, the Construction Industry Federation. 3200 Tweets of the top opinion leader were analyzed through graph metrics calculation, cluster analysis, sentiment analysis, and correlation analysis. The opinion leader used Twitter as a medium to disseminate the latest safety news. Thus, we may use Twitter to stimulate people’s interest on construction safety topics, share construction safety knowledge, opinions and ideas. Besides, our results showed that sentiment valence had no correlation with number of favorites or retweets. Nevertheless, there was a positive correlation between favorites and retweets.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Article number

105411

Pages from-to (Number of pages)

Pages 105411

Journal (Volume, Issue Number)

Safety Science (Volume 143)

Publication milestones

  • Accepted/In press - 07/07/2021
  • Published - 28/07/2021

Publication status

Published - 28/07/2021

ISSN

0925-7535

External Publication IDs

  • handle.net: 10547/625062
  • Scopus: 85111263615

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