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

Molly Simis-Wilkinson; Haley Madden; David Lassen; Leona Yi Fan Su; Dominique Brossard; Dietram A. Scheufele; Michael A. Xenos

doi:10.1177/1075547018766557

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

Molly Simis-Wilkinson
, Haley Madden
, David Lassen
, Leona Yi Fan Su
, Dominique Brossard
, Dietram A. Scheufele
, Michael A. Xenos

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English (US)
Pages (from-to)	314-339
Number of pages	26
Journal	Science Communication
Volume	40
Issue number	3
DOIs	https://doi.org/10.1177/1075547018766557
State	Published - Jun 1 2018
Externally published	Yes

Keywords

Twitter
benign violation theory
humor
science communication
social media

ASJC Scopus subject areas

Sociology and Political Science

Online availability

10.1177/1075547018766557

Library availability

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title = "Scientists Joking on Social Media: An Empirical Analysis of \#overlyhonestmethods",

abstract = "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{\textquoteright}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.",

keywords = "Twitter, benign violation theory, humor, science communication, social media",

author = "Molly Simis-Wilkinson and Haley Madden and David Lassen and Su, \{Leona Yi Fan\} and Dominique Brossard and Scheufele, \{Dietram A.\} and Xenos, \{Michael A.\}",

note = "The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This material is based on work supported by a grant from the University of Wisconsin–Madison Nanoscale Science and Engineering Center in Templated Synthesis and Assembly at the Nanoscale (Grant No. SES-DMR-0832760).",

year = "2018",

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doi = "10.1177/1075547018766557",

language = "English (US)",

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AU - Simis-Wilkinson, Molly

AU - Madden, Haley

AU - Lassen, David

AU - Su, Leona Yi Fan

AU - Brossard, Dominique

AU - Scheufele, Dietram A.

AU - Xenos, Michael A.

N1 - The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This material is based on work supported by a grant from the University of Wisconsin–Madison Nanoscale Science and Engineering Center in Templated Synthesis and Assembly at the Nanoscale (Grant No. SES-DMR-0832760).

PY - 2018/6/1

Y1 - 2018/6/1

N2 - 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.

AB - 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.

KW - Twitter

KW - benign violation theory

KW - humor

KW - science communication

KW - social media

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UR - https://www.scopus.com/pages/publications/85044956330#tab=citedBy

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

Abstract

Keywords

ASJC Scopus subject areas

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