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Who posts scientific tweets? An investigation into the productivity, locations, and identities of scientific tweeters

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  • Yu, Houqiang
  • Xiao, Tingting
  • Xu, Shenmeng
  • Wang, Yuefen

Abstract

Twitter altmetrics has been proposed to measure the popularity and the potential societal impact of scientific products, but scientific tweeters who produce the Twitter altmetrics data have not been well explored. The study, by analyzing 2.63 million scientific tweeters’ data that are extracted from the Altmetric.com company dataset, is aimed to reveal their productivity and geographic distribution in a comprehensive way. To gain a more in-depth understanding of their account types and identities, 1468 scientific tweeters of different levels of activeness are sampled for further analysis. Our results show that: (1) The extent to which a small proportion of tweeters have posted most of scientific tweets increases over time. In 2016, 10% of scientific tweeters have posted 80% of scientific tweets; (2) Scientific tweeters are widely distributed around the world but in a different pattern with the distribution of general Twitter users. In addition, scientific tweeters are found to be more active in tweeting scientific products than retweeting them in certain areas. (3) Manual coding of the sampled tweeters shows that the percentage of bot accounts among scientific tweeters is 1.8%, which is much lower than that among general Twitter users. Moreover, 73% of scientific tweeters use Twitter for professional purpose, 76% use real names for their accounts, and 16% are institutional accounts. (4) Identities of scientific tweeters are diversified. 49% of them are researchers among which university faculty is the major type, and 38% of them are the general public. With these results we suggest number of scientific tweets is not a good indicator of measuring either popularity or impact, tweeter’s productivity, location and identities must be taken into consideration in interpreting the meaning of Twitter altmetrics.

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  • Yu, Houqiang & Xiao, Tingting & Xu, Shenmeng & Wang, Yuefen, 2019. "Who posts scientific tweets? An investigation into the productivity, locations, and identities of scientific tweeters," Journal of Informetrics, Elsevier, vol. 13(3), pages 841-855.
  • Handle: RePEc:eee:infome:v:13:y:2019:i:3:p:841-855
    DOI: 10.1016/j.joi.2019.08.001
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    1. Houqiang Yu, 2017. "Context of altmetrics data matters: an investigation of count type and user category," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 267-283, April.
    2. Lutz Bornmann, 2016. "What do altmetrics counts mean? A plea for content analyses," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 1016-1017, April.
    3. Shenmeng Xu & Houqiang Yu & Bradley M. Hemminger & Xie Dong, 2018. "Who, what, why? An exploration of JoVE scientific video publications in tweets," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 845-856, November.
    4. Kim Holmberg & Mike Thelwall, 2014. "Disciplinary differences in Twitter scholarly communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1027-1042, November.
    5. Gorraiz, Juan & Melero-Fuentes, David & Gumpenberger, Christian & Valderrama-Zurián, Juan-Carlos, 2016. "Availability of digital object identifiers (DOIs) in Web of Science and Scopus," Journal of Informetrics, Elsevier, vol. 10(1), pages 98-109.
    6. Yu, Houqiang & Xu, Shenmeng & Xiao, Tingting & Hemminger, Brad M. & Yang, Siluo, 2017. "Global science discussed in local altmetrics: Weibo and its comparison with Twitter," Journal of Informetrics, Elsevier, vol. 11(2), pages 466-482.
    7. Stefanie Haustein & Timothy D. Bowman & Kim Holmberg & Andrew Tsou & Cassidy R. Sugimoto & Vincent Larivière, 2016. "Tweets as impact indicators: Examining the implications of automated “bot” accounts on Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(1), pages 232-238, January.
    8. Richard Van Noorden, 2014. "Online collaboration: Scientists and the social network," Nature, Nature, vol. 512(7513), pages 126-129, August.
    9. Stefanie Haustein & Isabella Peters & Cassidy R. Sugimoto & Mike Thelwall & Vincent Larivière, 2014. "Tweeting biomedicine: An analysis of tweets and citations in the biomedical literature," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 656-669, April.
    10. Rodrigo Costas & Zohreh Zahedi & Paul Wouters, 2015. "Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(10), pages 2003-2019, October.
    11. Zohreh Zahedi & Rodrigo Costas & Paul Wouters, 2017. "Mendeley readership as a filtering tool to identify highly cited publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(10), pages 2511-2521, October.
    12. Julia Vainio & Kim Holmberg, 2017. "Highly tweeted science articles: who tweets them? An analysis of Twitter user profile descriptions," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 345-366, July.
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    7. David Howoldt & Henning Kroll & Peter Neuhäusler & Alexander Feidenheimer, 2023. "Understanding researchers’ Twitter uptake, activity and popularity—an analysis of applied research in Germany," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 325-344, January.
    8. Zhichao Fang & Rodrigo Costas & Wencan Tian & Xianwen Wang & Paul Wouters, 2021. "How is science clicked on Twitter? Click metrics for Bitly short links to scientific publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(7), pages 918-932, July.
    9. Apostolidis, Chrysostomos & Devine, Anthony & Jabbar, Abdul, 2022. "From chalk to clicks – The impact of (rapid) technology adoption on employee emotions in the higher education sector," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
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