Abstract

Social media platforms are increasingly part of the academic workflow. However, there is a lack of research that examines these activities, particularly at the author level. This paper explores the activity of researchers in the Twittersphere by analyzing a large database of Web of Science authors systematically identified on Twitter using data from Altmetric.com. Using this information, this paper explores and compares patterns of tweeted and self-tweeted publications with other academic activities, such as citations, self-citations, and authorship at the author level. This paper also compares the thematic orientation among these different activities by analyzing the similarity of the research topics of the publications tweeted, cited, and authored. The results show that the productivity and impact of researchers, as defined by conventional bibliometric indicators, are not correlated to their popularity on the Twitter platform and that scholars generally tend to tweet about topics closely related to the publications they author and cite. These findings suggest that social media metrics capture a broader aspect of the academic workflow that is most likely related to science communication, dissemination, and engagement with wider audiences and that differs from conventional forms of impact as captured by citations. Areas for further exploration are also proposed.1

Highlights

  • Social media platforms provide opportunities to study science communication and the dissemination of research online (e.g., Priem, Taraborelli, Groth & Neylon 2010; Haustein, Peters, Sugimoto, Thelwall & Larivière 2014)

  • With the results obtained by Martín-Martín et al (2018) in their study of 240 bibliometricians on Twitter, who did not find a strong correlation between scholarly metrics and the numbers of tweets and followers of researchers

  • These results confirm earlier findings that Twitter uptake is higher among younger academics and that Twitter indicators are empirically different from scientometric indicators (Wouters et al 2018) and are not correlated with production and citation impact (Haustein et al 2014)

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Summary

Introduction

Social media platforms provide opportunities to study science communication and the dissemination of research online (e.g., Priem, Taraborelli, Groth & Neylon 2010; Haustein, Peters, Sugimoto, Thelwall & Larivière 2014). To compare these different types of activities, we calculate the cosine similarity between the papers authored, cited, and tweeted at the researcher level We discuss how such comparisons can provide insights into the academic and social media activities of researchers. This work takes advantage of a large set of disambiguated authors (Caron & van Eck 2014)—available in the Centre for Science and Technology Studies (CWTS) in-house version of the Web of Science (WoS) database—paired with their Twitter accounts (for details, see Costas et al 2020) This approach helps to bridge the gap left by earlier research that examined the presence of academics on Twitter (e.g., Ke et al 2017) but did not compare the Twitter activities of researchers with their bibliometric activities. Some of our results are discussed in the context of the symbolic capital theory (Bourdieu 2001), in particular that the use of social media can be related to novel forms of symbolic capital (Desrochers et al 2015), which differs from other types of scientific capital, such as authorship, citations, or acknowledgments (Cronin & Weaver 1995; Desrochers et al 2015)

Data and Methods
Publication-level indicators
Individual-level indicators
Self-mention indicators
Topic-level similarity indicators
A B A B n
Results
Discussion and Conclusions

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