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4118ccm云顶集团:【学术讲座】Covid-19 discussions on Twitter: Identifying key issues

2022-01-07 09:10

2022年1月6日4118ccm云顶集团信息资源研究中心和国际信息科学与技术学会ASIS&T SIG-KM拟共同举办网络研讨会,邀请Mike Thelwall教授开展讲座Covid-19 discussions on Twitter: Identifying key issues,欢迎各位老师和同学在线参加!

主讲人:Mike Thelwall教授

(Journal of the Association for Information Science and Technology副主编)

主题:Covid-19 discussions on Twitter: Identifying key issues

时 间:2022年1月6日21:00-22:00

地 点:腾讯会议室(ID: 139-918-042)



This webinar will talk about discussions of Covid-19 on Twitter, summarizing four studies and emphasizing the methods used to investigate Twitter. The first (Thelwall & Thelwall, 2020) identifies Covid-19 related themes that resonated on English language Twitter by investigating the most retweeted topics. Popular tweets in the strange situation of the first lockdowns helped build support for social distancing, criticized governments, supported key workers, supported others through social isolation. The second (Thelwall, 2021a) reports a retrospective analysis of the level of interest in Covid-19 vaccines on Twitter, showing that the Pfizer-BioNTech phase 3 trials results were the key event that converted this from a minor to major issue. The third (Thelwall et al., 2021) investigates how Covid-19 vaccine hesitancy was expressed up to 5 December 2020, finding that it was mostly tweeted about by right-wingers, with some exceptions. The final paper (Thelwall, 2021b) found international differences in English language tweeting about Covid-19 vaccinations from 5 December 2020 to 21 March 2021. Not all countries had prominent unofficial experts providing commentary and the concept of vaccine kindness (#VaccineMaitri) was only expressed in India. The talk will explain how Twitter became much easier to research at the start of 2021 when academics were allowed free access to historical tweets. It will discuss the word association thematic analysis method (Thelwall, 2021c) used to identify key themes within large collections of tweets from this source.


Mike Thelwall 是英国University of Wolverhampton 的数据科学教授。他从社会科学角度将数据科学方法应用于社交媒体度量、情感分析、网络计量等领域,为推特、社交网络、Youtube和各类链接与影响测度开发了量化网络方法,为联合国开发计划署(UNDP)等组织进行了影响力评估。他是负责任的研究度量英国论坛(the UK Forum for Responsible Research Metrics)成员、Journal of the Association for Information Science and Technology 副主编,出版4部著作,发表410篇期刊论文,2017-2021连续五年被评为全球社会科学高被引研究者,入选斯坦福大学发布的全球前2%顶尖科学家榜单,在Information & Library Science分类榜单中排名前二。





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