Scientists Joking on Social Media: An Empirical Analysis of #overlyhonestmethods

Scientists Joking on Social Media: An Empirical Analysis of #overlyhonestmethods
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科学家在社交媒体上开玩笑:实证分析

DOI:
10.1177/1075547018766557
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发表时间:
2018
影响因子:
9
通讯作者:
Michael A. Xenos
Michael A. Xenos
中科院分区:
人文科学2区
文献类型:
--
作者:
Molly Simis;Haley C. Madden;David Lassen;Leona Yi;D. Brossard;Dietram A. Scheufele;Michael A. Xenos

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推特上的#过度诚实的方法趋势被许多科学家用来揭开他们工作的帷幕,分享对研究世界的观察和见解。我们使用计算机辅助编码来评估从2013年1月7日标签诞生到2016年1月6日58,125#过度诚实的方法帖子的主题。此外,我们还手动编码了推文普查的随机样本,以评估所使用的幽默类型,以及笑话的目标和语言的排他性。我们提供了对这种自嘲的内部对话的分析,并对相关的伦理影响进行了评估。
The #overlyhonestmethods trend on Twitter is a space used by many scientists to peel back the curtain on their work and share observations and insights into the research world. We employ computer-assisted coding to assess the themes of 58,125 #overlyhonestmethods posts from January 7, 2013—the hashtag’s inception—to January 6, 2016. We additionally manually code a random sample of the census of tweets to evaluate the types of humor employed, as well as the targets of jokes and exclusivity of language. We offer analyses of this self-deprecating, insider conversation and an assessment of the associated ethical implications.