IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v120y2019i1d10.1007_s11192-019-03112-0.html
   My bibliography  Save this article

Mining network-level properties of Twitter altmetrics data

Author

Listed:
  • Anwar Said

    (Information Technology University)

  • Timothy D. Bowman

    (Wayne State University)

  • Rabeeh Ayaz Abbasi

    (Quaid-i-Azam University)

  • Naif Radi Aljohani

    (King Abdulaziz University)

  • Saeed-Ul Hassan

    (Information Technology University)

  • Raheel Nawaz

    (Manchester Metropolitan University)

Abstract

Social networking sites play a significant role in altmetrics. While 90% of all altmetric mentions come from Twitter, the known microscopic and macroscopic properties of Twitter altmetrics data are limited. In this study, we present a large-scale analysis of Twitter altmetrics data using social network analysis techniques on the ‘mention’ network of Twitter users. Exploiting the network-level properties of over 1.4 million tweets, corresponding to 77,757 scholarly articles, this study focuses on the following aspects of Twitter altmetrics data: (a) the influence of organizational accounts; (b) the formation of disciplinary communities; (c) the cross-disciplinary interaction among Twitter users; (d) the network motifs of influential Twitter users; and (e) testing the small-world property. The results show that Twitter-based social media communities have unique characteristics, which may affect social media usage counts either directly or indirectly. Therefore, instead of treating altmetrics data as a black box, the underlying social media networks, which may either inflate or deflate social media usage counts, need further scrutiny.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:120:y:2019:i:1:d:10.1007_s11192-019-03112-0
    DOI: 10.1007/s11192-019-03112-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03112-0
    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/s11192-019-03112-0?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. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Christian Pieter Hoffmann & Christoph Lutz & Miriam Meckel, 2016. "A relational altmetric? Network centrality on ResearchGate as an indicator of scientific impact," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 765-775, April.
    3. Lutz Bornmann & Robin Haunschild, 2018. "Allegation of scientific misconduct increases Twitter attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 1097-1100, May.
    4. 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.
    5. Yan, Weiwei & Zhang, Yin, 2018. "Research universities on the ResearchGate social networking site: An examination of institutional differences, research activity level, and social networks formed," Journal of Informetrics, Elsevier, vol. 12(1), pages 385-400.
    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. 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.
    9. 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.
    10. Fereshteh Didegah & Mike Thelwall, 2018. "Co‐saved, co‐tweeted, and co‐cited networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(8), pages 959-973, August.
    11. Adam Dinsmore & Liz Allen & Kevin Dolby, 2014. "Alternative Perspectives on Impact: The Potential of ALMs and Altmetrics to Inform Funders about Research Impact," PLOS Biology, Public Library of Science, vol. 12(11), pages 1-4, November.
    12. Heather Piwowar, 2013. "Value all research products," Nature, Nature, vol. 493(7431), pages 159-159, January.
    13. Zahedi, Zohreh & Haustein, Stefanie, 2018. "On the relationships between bibliographic characteristics of scientific documents and citation and Mendeley readership counts: A large-scale analysis of Web of Science publications," Journal of Informetrics, Elsevier, vol. 12(1), pages 191-202.
    14. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
    15. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    16. Thelwall, Mike & Nevill, Tamara, 2018. "Could scientists use Altmetric.com scores to predict longer term citation counts?," Journal of Informetrics, Elsevier, vol. 12(1), pages 237-248.
    17. Haddawy, Peter & Hassan, Saeed-Ul & Asghar, Awais & Amin, Sarah, 2016. "A comprehensive examination of the relation of three citation-based journal metrics to expert judgment of journal quality," Journal of Informetrics, Elsevier, vol. 10(1), pages 162-173.
    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. Saeed-Ul Hassan & Sehrish Iqbal & Naif R. Aljohani & Salem Alelyani & Alesia Zuccala, 2020. "Introducing the ‘alt-index’ for measuring the social visibility of scientific research," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(3), pages 1407-1419, June.
    2. 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.
    3. Jingfang Liu & Yafei Liu, 2022. "Exploring the User Interaction Network in an Anxiety Disorder Online Community: An Exponential Random Graph Model with Topical and Emotional Effects," IJERPH, MDPI, vol. 19(11), pages 1-13, May.
    4. Weiwei Yan & Qian Liu & Ruoyu Chen & Shengwei Yi, 2020. "Social networks formed by follower–followee relationships on academic social networking sites: an examination of corporation users," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2083-2101, September.
    5. 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.
    6. 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.
    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. Sergio Copiello, 2020. "Other than detecting impact in advance, alternative metrics could act as early warning signs of retractions: tentative findings of a study into the papers retracted by PLoS ONE," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2449-2469, December.
    9. Saeed-Ul Hassan & Naif R. Aljohani & Mudassir Shabbir & Umair Ali & Sehrish Iqbal & Raheem Sarwar & Eugenio Martínez-Cámara & Sebastián Ventura & Francisco Herrera, 2020. "Tweet Coupling: a social media methodology for clustering scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 973-991, August.
    10. 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.
    11. 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.

    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. Kong, Ling & Wang, Dongbo, 2020. "Comparison of citations and attention of cover and non-cover papers," Journal of Informetrics, Elsevier, vol. 14(4).
    2. Sergio Copiello, 2020. "Other than detecting impact in advance, alternative metrics could act as early warning signs of retractions: tentative findings of a study into the papers retracted by PLoS ONE," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2449-2469, December.
    3. Sergio Copiello, 2019. "Research Interest: another undisclosed (and redundant) algorithm by ResearchGate," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 351-360, July.
    4. 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.
    5. Sergio Copiello & Pietro Bonifaci, 2019. "ResearchGate Score, full-text research items, and full-text reads: a follow-up study," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1255-1262, May.
    6. Cristina López-Duarte & Marta M. Vidal-Suárez & Belén González-Díaz, 2019. "Cross-national distance and international business: an analysis of the most influential recent models," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 173-208, October.
    7. Kaltrina Nuredini, 2021. "Investigating Altmetric Information For The Top 1000 Journals From Handelsblatt Ranking In Economic And Business Studies," Journal of Economic Surveys, Wiley Blackwell, vol. 35(5), pages 1315-1343, December.
    8. 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.
    9. 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.
    10. Saeed-Ul Hassan & Naif R. Aljohani & Mudassir Shabbir & Umair Ali & Sehrish Iqbal & Raheem Sarwar & Eugenio Martínez-Cámara & Sebastián Ventura & Francisco Herrera, 2020. "Tweet Coupling: a social media methodology for clustering scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 973-991, August.
    11. Saeed-Ul Hassan & Sehrish Iqbal & Naif R. Aljohani & Salem Alelyani & Alesia Zuccala, 2020. "Introducing the ‘alt-index’ for measuring the social visibility of scientific research," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(3), pages 1407-1419, June.
    12. 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).
    13. Ying Guo & Xiantao Xiao, 2022. "Author-level altmetrics for the evaluation of Chinese scholars," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 973-990, February.
    14. Walters, William H., 2017. "Do subjective journal ratings represent whole journals or typical articles? Unweighted or weighted citation impact?," Journal of Informetrics, Elsevier, vol. 11(3), pages 730-744.
    15. Xiaolan Wu & Chengzhi Zhang, 2019. "Finding high-impact interdisciplinary users based on friend discipline distribution in academic social networking sites," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1017-1035, May.
    16. Lutz Bornmann & Robin Haunschild & Vanash M Patel, 2020. "Are papers addressing certain diseases perceived where these diseases are prevalent? The proposal to use Twitter data as social-spatial sensors," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-22, November.
    17. Xu, Fang & Ou, Guiyan & Ma, Tingcan & Wang, Xianwen, 2021. "The consistency of impact of preprints and their journal publications," Journal of Informetrics, Elsevier, vol. 15(2).
    18. Rafael Repiso & Antonio Castillo-Esparcia & Daniel Torres-Salinas, 2019. "Altmetrics, alternative indicators for Web of Science Communication studies journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 941-958, May.
    19. Łukasz Wiechetek & Zbigniew Pastuszak, 2022. "Academic social networks metrics: an effective indicator for university performance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1381-1401, March.
    20. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.

    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:120:y:2019:i:1:d:10.1007_s11192-019-03112-0. 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.