IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v128y2023i10d10.1007_s11192-023-04799-y.html
   My bibliography  Save this article

Relating popularity on Twitter and Linkedin to bibliometric indicators of visibility and interconnectedness: an analysis of 8512 applied researchers in Germany

Author

Listed:
  • David Howoldt

    (Independent Researcher)

  • Henning Kroll

    (Fraunhofer Institute for Systems and Innovation Research
    Leibniz Universität Hannover)

  • Peter Neuhäusler

    (Fraunhofer Institute for Systems and Innovation Research
    Technische Universität Berlin)

Abstract

We analyse the degree to which the popularity of scientific authors on Twitter and LinkedIn corresponds to publication-based indicators as to their visibility and interconnectedness. Departing from the extant literature’s focus on the visibility of individual papers, we turn to the popularity of individuals on social media platforms. We explore whether this popularity is reflected in the visibility that researchers achieve and the collaborations they maintain in the publication domain. Studying a large sample of applied researchers in Germany, we find congruence between researchers’ popularity on social media, and both their visibility and interconnectedness in the publication domain. Comparing the effects of Twitter and LinkedIn engagement, we furthermore find that the characteristics of this relationship are associated with the intended function of the social media platform in which researchers engage. We conclude that social media platforms are a relevant channel of academic communication, alongside existing channels of formal and informal exchange.

Suggested Citation

  • David Howoldt & Henning Kroll & Peter Neuhäusler, 2023. "Relating popularity on Twitter and Linkedin to bibliometric indicators of visibility and interconnectedness: an analysis of 8512 applied researchers in Germany," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5571-5594, October.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:10:d:10.1007_s11192-023-04799-y
    DOI: 10.1007/s11192-023-04799-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-023-04799-y
    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/s11192-023-04799-y?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. 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.
    2. Abbasi, Alireza & Hossain, Liaquat & Leydesdorff, Loet, 2012. "Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks," Journal of Informetrics, Elsevier, vol. 6(3), pages 403-412.
    3. Sen Chai & Richard B. Freeman, 2019. "Temporary colocation and collaborative discovery: Who confers at conferences," Strategic Management Journal, Wiley Blackwell, vol. 40(13), pages 2138-2164, December.
    4. José Luis Ortega, 2016. "To be or not to be on Twitter, and its relationship with the tweeting and citation of research papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1353-1364, November.
    5. Miguel-Angel Vera-Baceta & Michael Thelwall & Kayvan Kousha, 2019. "Web of Science and Scopus language coverage," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1803-1813, December.
    6. Kim Holmberg & Mike Thelwall, 2014. "Disciplinary differences in Twitter scholarly communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1027-1042, November.
    7. Xianwen Wang & Zhichao Fang & Xinhui Guo, 2016. "Tracking the digital footprints to scholarly articles from social media," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1365-1376, November.
    8. Gorodnichenko, Yuriy & Pham, Tho & Talavera, Oleksandr, 2021. "Conference presentations and academic publishing," Economic Modelling, Elsevier, vol. 95(C), pages 228-254.
    9. Jiancheng Guan & Yan Yan & Jingjing Zhang, 2015. "How do collaborative features affect scientific output? Evidences from wind power field," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 333-355, January.
    10. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
    11. Abbasi, Alireza & Altmann, Jörn & Hossain, Liaquat, 2011. "Identifying the effects of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance measures and social network analysis measures," Journal of Informetrics, Elsevier, vol. 5(4), pages 594-607.
    12. Cassidy R. Sugimoto & Sam Work & Vincent Larivière & Stefanie Haustein, 2017. "Scholarly use of social media and altmetrics: A review of the literature," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(9), pages 2037-2062, September.
    13. Samara Klar & Yanna Krupnikov & John Barry Ryan & Kathleen Searles & Yotam Shmargad, 2020. "Using social media to promote academic research: Identifying the benefits of twitter for sharing academic work," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-15, April.
    14. Giuliana Viglione, 2020. "How scientific conferences will survive the coronavirus shock," Nature, Nature, vol. 582(7811), pages 166-167, June.
    15. J. Scott Long & Jeremy Freese, 2006. "Regression Models for Categorical Dependent Variables using Stata, 2nd Edition," Stata Press books, StataCorp LP, edition 2, number long2, March.
    16. Georg Franck, 2002. "The scientific economy of attention: A novel approach to the collective rationality of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(1), pages 3-26, September.
    17. Andre Torre & Alain Rallet, 2005. "Proximity and Localization," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 47-59.
    18. Waverly W. Ding & Sharon G. Levin & Paula E. Stephan & Anne E. Winkler, 2010. "The Impact of Information Technology on Academic Scientists' Productivity and Collaboration Patterns," Management Science, INFORMS, vol. 56(9), pages 1439-1461, September.
    19. 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.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Henning Kroll & Peter Neuhäusler, 2022. "“Formal and informal networkedness among German Academics”: exploring the role of conferences and co-publications in scientific performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6431-6452, November.
    3. Marian-Gabriel Hâncean & Matjaž Perc & Jürgen Lerner, 2021. "The coauthorship networks of the most productive European researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 201-224, January.
    4. 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.
    5. Shanwu Tian & Xiurui Xu & Ping Li, 2021. "Acknowledgement network and citation count: the moderating role of collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7837-7857, September.
    6. Siluo Yang & Xin Xing & Fan Qi & Maria Cláudia Cabrini Grácio, 2021. "Comparison of academic book impact from a disciplinary perspective: an analysis of citations and altmetric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1101-1123, February.
    7. Liwei Zhang & Jue Wang, 2021. "What affects publications’ popularity on Twitter?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9185-9198, November.
    8. Martín-Martín, Alberto & Orduna-Malea, Enrique & Delgado López-Cózar, Emilio, 2018. "Author-level metrics in the new academic profile platforms: The online behaviour of the Bibliometrics community," Journal of Informetrics, Elsevier, vol. 12(2), pages 494-509.
    9. Guan, Jiancheng & Yan, Yan & Zhang, Jing Jing, 2017. "The impact of collaboration and knowledge networks on citations," Journal of Informetrics, Elsevier, vol. 11(2), pages 407-422.
    10. Stefano Scarazzati & Lili Wang, 2019. "The effect of collaborations on scientific research output: the case of nanoscience in Chinese regions," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 839-868, November.
    11. Jianhua Hou & Jiantao Ye, 2020. "Are uncited papers necessarily all nonimpact papers? A quantitative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1631-1662, August.
    12. Jianhua Hou & Bili Zheng & Yang Zhang & Chaomei Chen, 2021. "How do Price medalists’ scholarly impact change before and after their awards?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5945-5981, July.
    13. Cao, Renmeng & Geng, Yu & Xu, Xiaoke & Wang, Xianwen, 2022. "How does duplicate tweeting boost social media exposure to scholarly articles?," Journal of Informetrics, Elsevier, vol. 16(1).
    14. 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.
    15. Xi Zhang & Xianhai Wang & Hongke Zhao & Patricia Ordóñez de Pablos & Yongqiang Sun & Hui Xiong, 2019. "An effectiveness analysis of altmetrics indices for different levels of artificial intelligence publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1311-1344, June.
    16. José Luis Ortega, 2018. "Reliability and accuracy of altmetric providers: a comparison among Altmetric.com, PlumX and Crossref Event Data," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 2123-2138, September.
    17. Pantea Kamrani & Isabelle Dorsch & Wolfgang G. Stock, 2021. "Do researchers know what the h-index is? And how do they estimate its importance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5489-5508, July.
    18. Thelwall, Mike, 2018. "Dimensions: A competitor to Scopus and the Web of Science?," Journal of Informetrics, Elsevier, vol. 12(2), pages 430-435.
    19. Mike Thelwall, 2021. "Alternative medicines worth researching? Citation analyses of acupuncture, chiropractic, homeopathy, and osteopathy 1996–2017," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8731-8747, October.
    20. Ali Najmi & Taha H. Rashidi & Alireza Abbasi & S. Travis Waller, 2017. "Reviewing the transport domain: an evolutionary bibliometrics and network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 843-865, February.

    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:128:y:2023:i:10:d:10.1007_s11192-023-04799-y. 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.