IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0242550.html
   My bibliography  Save this article

Are papers addressing certain diseases perceived where these diseases are prevalent? The proposal to use Twitter data as social-spatial sensors

Author

Listed:
  • Lutz Bornmann
  • Robin Haunschild
  • Vanash M Patel

Abstract

We propose to use Twitter data as social-spatial sensors. This study deals with the question whether research papers on certain diseases are perceived by people in regions (worldwide) that are especially concerned by these diseases. Since (some) Twitter data contain location information, it is possible to spatially map the activity of Twitter users referring to certain papers (e.g., dealing with tuberculosis). The resulting maps reveal whether heavy activity on Twitter is correlated with large numbers of people having certain diseases. In this study, we focus on tuberculosis, human immunodeficiency virus (HIV), and malaria, since the World Health Organization ranks these diseases as the top three causes of death worldwide by a single infectious agent. The results of the social-spatial Twitter maps (and additionally performed regression models) reveal the usefulness of the proposed sensor approach. One receives an impression of how research papers on the diseases have been perceived by people in regions that are especially concerned by these diseases. Our study demonstrates a promising approach for using Twitter data for research evaluation purposes beyond simple counting of tweets.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0242550
    DOI: 10.1371/journal.pone.0242550
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242550
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0242550&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0242550?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
    ---><---

    References listed on IDEAS

    as
    1. Bornmann, Lutz & Haunschild, Robin & Adams, Jonathan, 2019. "Do altmetrics assess societal impact in a comparable way to case studies? An empirical test of the convergent validity of altmetrics based on data from the UK research excellence framework (REF)," Journal of Informetrics, Elsevier, vol. 13(1), pages 325-340.
    2. 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.
    3. Zhang, Lin & ZHAO, Wenjing & Liu, Jianhua & Sivertsen, Gunnar & HUANG, Ying, 2020. "Do national funding organizations properly address the diseases with the highest burden? - Observations from China and the UK," SocArXiv ckpf8, Center for Open Science.
    4. Lin Zhang & Wenjing Zhao & Jianhua Liu & Gunnar Sivertsen & Ying Huang, 2020. "Do national funding organizations properly address the diseases with the highest burden?: Observations from China and the UK," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1733-1761, November.
    5. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    6. Jeffrey Shaman & Alicia Karspeck & Wan Yang & James Tamerius & Marc Lipsitch, 2013. "Real-time influenza forecasts during the 2012–2013 season," Nature Communications, Nature, vol. 4(1), pages 1-10, December.
    7. Ludo Waltman & Rodrigo Costas, 2014. "F1000 Recommendations as a Potential New Data Source for Research Evaluation: A Comparison With Citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(3), pages 433-445, March.
    8. repec:aph:ajpbhl:10.2105/ajph.2016.303512_4 is not listed on IDEAS
    9. 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.
    10. Zohreh Zahedi & Rodrigo Costas & Paul Wouters, 2014. "How well developed are altmetrics? A cross-disciplinary analysis of the presence of ‘alternative metrics’ in scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1491-1513, November.
    11. Mojisola Erdt & Aarthy Nagarajan & Sei-Ching Joanna Sin & Yin-Leng Theng, 2016. "Altmetrics: an analysis of the state-of-the-art in measuring research impact on social media," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1117-1166, November.
    12. 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.
    13. Lutz Bornmann & Robin Haunschild, 2017. "Does evaluative scientometrics lose its main focus on scientific quality by the new orientation towards societal impact?," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 937-943, February.
    14. Lutz Bornmann, 2015. "Alternative metrics in scientometrics: a meta-analysis of research into three altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 1123-1144, June.
    15. Björn Hammarfelt, 2014. "Using altmetrics for assessing research impact in the humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1419-1430, November.
    16. 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.
    17. Sinnenberg, L. & Buttenheim, A.M. & Padrez, K. & Mancheno, C. & Ungar, L. & Merchant, R.M., 2017. "Twitter as a tool for health research: A systematic review," American Journal of Public Health, American Public Health Association, vol. 107(1), pages 1-8.
    18. 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.
    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. Haunschild, Robin & Bornmann, Lutz, 2023. "Which papers cited which tweets? An exploratory analysis based on Scopus data," Journal of Informetrics, Elsevier, vol. 17(2).

    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. 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.
    2. Bornmann, Lutz & Haunschild, Robin & Adams, Jonathan, 2019. "Do altmetrics assess societal impact in a comparable way to case studies? An empirical test of the convergent validity of altmetrics based on data from the UK research excellence framework (REF)," Journal of Informetrics, Elsevier, vol. 13(1), pages 325-340.
    3. Bornmann, Lutz & Haunschild, Robin, 2018. "Normalization of zero-inflated data: An empirical analysis of a new indicator family and its use with altmetrics data," Journal of Informetrics, Elsevier, vol. 12(3), pages 998-1011.
    4. 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.
    5. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    6. Lutz Bornmann & Rüdiger Mutz & Robin Haunschild & Felix Moya-Anegon & Mirko Almeida Madeira Clemente & Moritz Stefaner, 2021. "Mapping the impact of papers on various status groups in excellencemapping.net: a new release of the excellence mapping tool based on citation and reader scores," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9305-9331, November.
    7. Jianhua Hou & Xiucai Yang & Yang Zhang, 2023. "The effect of social media knowledge cascade: an analysis of scientific papers diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5169-5195, September.
    8. Sergio Copiello, 2019. "Research Interest: another undisclosed (and redundant) algorithm by ResearchGate," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 351-360, July.
    9. Chieh Liu & Mu-Hsuan Huang, 2022. "Exploring the relationships between altmetric counts and citations of papers in different academic fields based on co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4939-4958, August.
    10. 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.
    11. António Correia & Hugo Paredes & Benjamim Fonseca, 2018. "Scientometric analysis of scientific publications in CSCW," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 31-89, January.
    12. Christine Meschede & Tobias Siebenlist, 2018. "Cross-metric compatability and inconsistencies of altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 283-297, April.
    13. de Carvalho, Gustavo Dambiski Gomes & Sokulski, Carla Cristiane & da Silva, Wesley Vieira & de Carvalho, Hélio Gomes & de Moura, Rafael Vignoli & de Francisco, Antonio Carlos & da Veiga, Claudimar Per, 2020. "Bibliometrics and systematic reviews: A comparison between the Proknow-C and the Methodi Ordinatio," Journal of Informetrics, Elsevier, vol. 14(3).
    14. 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).
    15. Ni Cheng & Ke Dong, 2018. "Knowledge communication on social media: a case study of Biomedical Science on Baidu Baike," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1749-1770, September.
    16. Lin Zhang & Zhenyu Gou & Zhichao Fang & Gunnar Sivertsen & Ying Huang, 2023. "Who tweets scientific publications? A large‐scale study of tweeting audiences in all areas of research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(13), pages 1485-1497, December.
    17. 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.
    18. Isidro F. Aguillo, 2020. "Altmetrics of the Open Access Institutional Repositories: a webometrics approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(3), pages 1181-1192, June.
    19. 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.
    20. Mohammadamin Erfanmanesh & A. Noorhidawati & A. Abrizah, 2019. "What can Bookmetrix tell us about the impact of Springer Nature’s books," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 521-536, October.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0242550. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.