IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i8d10.1007_s11192-022-04468-6.html
   My bibliography  Save this article

User engagement with scholarly tweets of scientific papers: a large-scale and cross-disciplinary analysis

Author

Listed:
  • Zhichao Fang

    (Renmin University of China
    Leiden University)

  • Rodrigo Costas

    (Leiden University
    Stellenbosch University)

  • Paul Wouters

    (Leiden University)

Abstract

This study investigates the extent to which scholarly tweets of scientific papers are engaged with by Twitter users through four types of user engagement behaviors, i.e., liking, retweeting, quoting, and replying. Based on a sample consisting of 7 million scholarly tweets of Web of Science papers, our results show that likes is the most prevalent engagement metric, covering 44% of scholarly tweets, followed by retweets (36%), whereas quotes and replies are only present for 9% and 7% of all scholarly tweets, respectively. From a disciplinary point of view, scholarly tweets in the field of Social Sciences and Humanities are more likely to trigger user engagement over other subject fields. The presence of user engagement is more associated with other Twitter-based factors (e.g., number of mentioned users in tweets and number of followers of users) than with science-based factors (e.g., citations and Mendeley readers of tweeted papers). Building on these findings, this study sheds light on the possibility to apply user engagement metrics in measuring deeper levels of Twitter reception of scholarly information.

Suggested Citation

  • Zhichao Fang & Rodrigo Costas & Paul Wouters, 2022. "User engagement with scholarly tweets of scientific papers: a large-scale and cross-disciplinary analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4523-4546, August.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:8:d:10.1007_s11192-022-04468-6
    DOI: 10.1007/s11192-022-04468-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-022-04468-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-022-04468-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yajie Wang & Alesia Zuccala, 2021. "Scholarly book publishers as publicity agents for SSH titles on Twitter," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4817-4840, June.
    2. Lutz Bornmann & Robin Haunschild, 2016. "How to normalize Twitter counts? A first attempt based on journals in the Twitter Index," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1405-1422, June.
    3. 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.
    4. Ronaldo Ferreira Araujo, 2020. "Communities of attention networks: introducing qualitative and conversational perspectives for altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1793-1809, September.
    5. 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.
    6. Haunschild, Robin & Leydesdorff, Loet & Bornmann, Lutz & Hellsten, Iina & Marx, Werner, 2019. "Does the public discuss other topics on climate change than researchers? A comparison of explorative networks based on author keywords and hashtags," Journal of Informetrics, Elsevier, vol. 13(2), pages 695-707.
    7. Didegah, Fereshteh & Mejlgaard, Niels & Sørensen, Mads P., 2018. "Investigating the quality of interactions and public engagement around scientific papers on Twitter," Journal of Informetrics, Elsevier, vol. 12(3), pages 960-971.
    8. Saeed-Ul Hassan & Timothy D. Bowman & Mudassir Shabbir & Aqsa Akhtar & Mubashir Imran & Naif Radi Aljohani, 2019. "Influential tweeters in relation to highly cited articles in altmetric big data," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 481-493, April.
    9. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    10. Zhichao Fang & Jonathan Dudek & Rodrigo Costas, 2022. "Facing the volatility of tweets in altmetric research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(8), pages 1192-1195, August.
    11. 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.
    12. 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.
    13. Zeileis, Achim & Kleiber, Christian & Jackman, Simon, 2008. "Regression Models for Count Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i08).
    14. Veronika Cheplygina & Felienne Hermans & Casper Albers & Natalia Bielczyk & Ionica Smeets, 2020. "Ten simple rules for getting started on Twitter as a scientist," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-9, February.
    15. Zhichao Fang & Rodrigo Costas & Wencan Tian & Xianwen Wang & Paul Wouters, 2020. "An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2519-2549, September.
    16. Kim Holmberg & Mike Thelwall, 2014. "Disciplinary differences in Twitter scholarly communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1027-1042, November.
    17. Rodrigo Costas & Sarah de Rijcke & Noortje Marres, 2021. "“Heterogeneous couplings”: Operationalizing network perspectives to study science‐society interactions through social media metrics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(5), pages 595-610, May.
    18. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    19. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    20. 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.
    21. Han Zheng & Htet Htet Aung & Mojisola Erdt & Tai‐Quan Peng & Aravind Sesagiri Raamkumar & Yin‐Leng Theng, 2019. "Social media presence of scholarly journals," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(3), pages 256-270, March.
    22. Zhichao Fang & Jonathan Dudek & Rodrigo Costas, 2020. "The stability of Twitter metrics: A study on unavailable Twitter mentions of scientific publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(12), pages 1455-1469, December.
    23. 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.
    24. Iina Hellsten & Loet Leydesdorff, 2020. "Automated analysis of actor–topic networks on twitter: New approaches to the analysis of socio‐semantic networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(1), pages 3-15, January.
    25. Anwar Said & Timothy D. Bowman & Rabeeh Ayaz Abbasi & Naif Radi Aljohani & Saeed-Ul Hassan & Raheel Nawaz, 2019. "Mining network-level properties of Twitter altmetrics data," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 217-235, July.
    26. 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.
    27. Sanmitra Bhattacharya & Padmini Srinivasan & Phil Polgreen, 2014. "Engagement with Health Agencies on Twitter," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-12, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. González-Betancor, Sara M. & Dorta-González, Pablo, 2023. "Does society show differential attention to researchers based on gender and field?," Journal of Informetrics, Elsevier, vol. 17(4).
    2. Chan, Ho Fai & Önder, Ali Sina & Schweitzer, Sascha & Torgler, Benno, 2023. "Twitter and citations," Economics Letters, Elsevier, vol. 231(C).
    3. Houqiang Yu & Yue Wang & Shah Hussain & Haoyang Song, 2023. "Towards a better understanding of Facebook Altmetrics in LIS field: assessing the characteristics of involved paper, user and post," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3147-3170, May.
    4. Haunschild, Robin & Bornmann, Lutz, 2023. "Which papers cited which tweets? An exploratory analysis based on Scopus data," Journal of Informetrics, Elsevier, vol. 17(2).
    5. Enrique Orduña-Malea & Cristina I. Font-Julián, 2022. "Are patents linked on Twitter? A case study of Google patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6339-6362, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Yaxue Ma & Zhichao Ba & Yuxiang Zhao & Jin Mao & Gang Li, 2021. "Understanding and predicting the dissemination of scientific papers on social media: a two-step simultaneous equation modeling–artificial neural network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7051-7085, August.
    3. Enrique Orduña-Malea & Cristina I. Font-Julián, 2022. "Are patents linked on Twitter? A case study of Google patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6339-6362, November.
    4. 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.
    5. Zhichao Fang & Rodrigo Costas & Wencan Tian & Xianwen Wang & Paul Wouters, 2020. "An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2519-2549, September.
    6. Dorte Drongstrup & Shafaq Malik & Naif Radi Aljohani & Salem Alelyani & Iqra Safder & Saeed-Ul Hassan, 2020. "Can social media usage of scientific literature predict journal indices of AJG, SNIP and JCR? An altmetric study of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1541-1558, November.
    7. Rodrigo Costas & Sarah de Rijcke & Noortje Marres, 2021. "“Heterogeneous couplings”: Operationalizing network perspectives to study science‐society interactions through social media metrics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(5), pages 595-610, May.
    8. Hou, Jianhua & Wang, Yuanyuan & Zhang, Yang & Wang, Dongyi, 2022. "How do scholars and non-scholars participate in dataset dissemination on Twitter," Journal of Informetrics, Elsevier, vol. 16(1).
    9. Didegah, Fereshteh & Mejlgaard, Niels & Sørensen, Mads P., 2018. "Investigating the quality of interactions and public engagement around scientific papers on Twitter," Journal of Informetrics, Elsevier, vol. 12(3), pages 960-971.
    10. Wenceslao Arroyo-Machado & Daniel Torres-Salinas & Nicolas Robinson-Garcia, 2021. "Identifying and characterizing social media communities: a socio-semantic network approach to altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9267-9289, November.
    11. Yingxin Estella Ye & Jin-Cheon Na & Poong Oh, 2022. "Are automated accounts driving scholarly communication on Twitter? a case study of dissemination of COVID-19 publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2151-2172, May.
    12. Houqiang Yu & Yue Wang & Shah Hussain & Haoyang Song, 2023. "Towards a better understanding of Facebook Altmetrics in LIS field: assessing the characteristics of involved paper, user and post," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3147-3170, May.
    13. Saeed-Ul Hassan & Mubashir Imran & Uzair Gillani & Naif Radi Aljohani & Timothy D. Bowman & Fereshteh Didegah, 2017. "Measuring social media activity of scientific literature: an exhaustive comparison of scopus and novel altmetrics big data," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1037-1057, November.
    14. Yu, Houqiang & Xu, Shenmeng & Xiao, Tingting, 2018. "Is there Lingua Franca in informal scientific communication? Evidence from language distribution of scientific tweets," Journal of Informetrics, Elsevier, vol. 12(3), pages 605-617.
    15. Daniel Torres-Salinas & Domingo Docampo & Wenceslao Arroyo-Machado & Nicolas Robinson-Garcia, 2024. "The many publics of science: using altmetrics to identify common communication channels by scientific field," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 3705-3723, July.
    16. 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.
    17. Liwei Zhang & Jue Wang, 2021. "What affects publications’ popularity on Twitter?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9185-9198, November.
    18. Wang, Yajie & Hou, Haiyan & Hu, Zhigang, 2021. "‘To tweet or not to tweet?’ A study of the use of Twitter by scholarly book publishers in Social Sciences and Humanities," Journal of Informetrics, Elsevier, vol. 15(3).
    19. João Melo Maricato & Bruno Lara Castro Manso, 2022. "Characterization of the communities of attention interacting with scientific papers on Twitter: altmetric analysis of a Brazilian University," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3815-3835, July.
    20. Amalia Mas-Bleda & Mike Thelwall, 2016. "Can alternative indicators overcome language biases in citation counts? A comparison of Spanish and UK research," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2007-2030, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:127:y:2022:i:8:d:10.1007_s11192-022-04468-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.