IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v128y2023i9d10.1007_s11192-023-04785-4.html
   My bibliography  Save this article

The effect of social media knowledge cascade: an analysis of scientific papers diffusion

Author

Listed:
  • Jianhua Hou

    (SUN Yat-Sen University)

  • Xiucai Yang

    (SUN Yat-Sen University)

  • Yang Zhang

    (SUN Yat-Sen University)

Abstract

Our goal is to reveal the social media knowledge cascade (SMKC) of the diffusion of scientific papers. PLoS Biology, one of the prestigious and influential open-access journals under PLoS, has received much attention from researchers. Using papers published in PLoS Biology as sample, we use the citation indicators and social media indicators of scientific papers to establish an SMKC network model that measures the relationship between the citation diffusion trajectory of scientific papers and their social media diffusion trajectory through knowledge bursts. Based on the number and type of knowledge bursts, we have identified three types of SMKCs: Social media and SMKC (S–S knowledge cascade), Citation and citation knowledge cascade (C–C knowledge cascade), and Social media and citation knowledge cascade (S–C knowledge cascade). Specifically, we focus on studying the S–C knowledge cascade type in SMKC. We explored the relationship between social media diffusion trajectory knowledge bursts and citation diffusion trajectory knowledge bursts, the prompting effect of S–C knowledge cascades on paper's citation and the pivot node characteristics of the paper S–C knowledge cascade. Our research found that, in the S–C knowledge cascade papers the knowledge burst of the paper on the social media diffusion trajectory is the decisive factor for the knowledge burst in the citation diffusion trajectory. Only part of the knowledge burst in the citation diffusion trajectory will immediately cause the social media diffusion trajectory knowledge bursts. The stronger a paper's SMKC, the easier it is to become a highly cited paper. The type of pivot node is more inclined to the burst of knowledge on the trajectory of social media diffusion. We analyzed the trajectory of knowledge dissemination in the life cycle of scientific papers from a dynamic perspective. We revealed the general features of SMKCs in the process of scientific paper diffusion.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:9:d:10.1007_s11192-023-04785-4
    DOI: 10.1007/s11192-023-04785-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-023-04785-4
    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/s11192-023-04785-4?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. Zhao, Qihang & Feng, Xiaodong, 2022. "Utilizing citation network structure to predict paper citation counts: A Deep learning approach," Journal of Informetrics, Elsevier, vol. 16(1).
    2. 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).
    3. Rodrigo Costas & Thed N. van Leeuwen & Anthony F.J. van Raan, 2010. "Is scientific literature subject to a ‘Sell‐By‐Date’? A general methodology to analyze the ‘durability’ of scientific documents," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(2), pages 329-339, February.
    4. Rodrigo Costas & Thed N. van Leeuwen & Anthony F.J. van Raan, 2010. "Is scientific literature subject to a ‘Sell-By-Date’? A general methodology to analyze the ‘durability’ of scientific documents," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(2), pages 329-339, February.
    5. Lachance, Christian & Larivière, Vincent, 2014. "On the citation lifecycle of papers with delayed recognition," Journal of Informetrics, Elsevier, vol. 8(4), pages 863-872.
    6. Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(3), pages 577-598.
    7. Yong Huang & Yi Bu & Ying Ding & Wei Lu, 2018. "Number versus structure: towards citing cascades," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 2177-2193, December.
    8. Lutz Bornmann, 2013. "What is societal impact of research and how can it be assessed? a literature survey," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(2), pages 217-233, February.
    9. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    10. Anderson, Lisa R & Holt, Charles A, 1997. "Information Cascades in the Laboratory," American Economic Review, American Economic Association, vol. 87(5), pages 847-862, December.
    11. Hendrik P. van Dalen & K?ne Henkens, 2005. "Signals in science - On the importance of signaling in gaining attention in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(2), pages 209-233, August.
    12. Werner Marx & Lutz Bornmann, 2014. "Tracing the origin of a scientific legend by reference publication year spectroscopy (RPYS): the legend of the Darwin finches," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 839-844, June.
    13. Jiang Li & Fred Y. Ye, 2012. "The phenomenon of all-elements-sleeping-beauties in scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(3), pages 795-799, September.
    14. Trueman, Brett, 1994. "Analyst Forecasts and Herding Behavior," The Review of Financial Studies, Society for Financial Studies, vol. 7(1), pages 97-124.
    15. Andrea Giovanni Nuzzolese & Paolo Ciancarini & Aldo Gangemi & Silvio Peroni & Francesco Poggi & Valentina Presutti, 2019. "Do altmetrics work for assessing research quality?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 539-562, February.
    16. Núria Bautista-Puig & Daniela De Filippo & Elba Mauleón & Elías Sanz-Casado, 2019. "Scientific Landscape of Citizen Science Publications: Dynamics, Content and Presence in Social Media," Publications, MDPI, vol. 7(1), pages 1-22, February.
    17. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    18. Guoqiang Liang & Haiyan Hou & Qiao Chen & Zhigang Hu, 2020. "Diffusion and adoption: an explanatory model of “question mark” and “rising star” articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 219-232, July.
    19. 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.
    20. Stoneman, Paul & Diederen, Paul, 1994. "Technology Diffusion and Public Policy," Economic Journal, Royal Economic Society, vol. 104(425), pages 918-930, July.
    21. 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.
    22. E. Garfield & I. H. Sher, 1963. "New factors in the evaluation of scientific literature through citation indexing," American Documentation, Wiley Blackwell, vol. 14(3), pages 195-201, July.
    23. Werner Marx & Lutz Bornmann & Andreas Barth & Loet Leydesdorff, 2014. "Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS)," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 751-764, April.
    24. Aurel Avramescu, 1979. "Actuality and Obsolescence of Scientific Literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 30(5), pages 296-303, September.
    25. Bornmann, Lutz & Leydesdorff, Loet, 2013. "The validation of (advanced) bibliometric indicators through peer assessments: A comparative study using data from InCites and F1000," Journal of Informetrics, Elsevier, vol. 7(2), pages 286-291.
    26. Katherine W. McCain, 1989. "Descriptor and citation retrieval in the Medical Behavioral Sciences literature: Retrieval overlaps and novelty distribution," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 40(2), pages 110-114, March.
    27. Lutz Bornmann & Robin Haunschild, 2018. "Do altmetrics correlate with the quality of papers? A large-scale empirical study based on F1000Prime data," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-12, May.
    28. 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.
    29. Jianhua Hou & Xiucai Yang, 2019. "Patent sleeping beauties: evolutionary trajectories and identification methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 187-215, July.
    30. Saeideh Ebrahimy & Jafar Mehrad & Fatemeh Setareh & Massoud Hosseinchari, 2016. "Path analysis of the relationship between visibility and citation: the mediating roles of save, discussion, and recommendation metrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1497-1510, December.
    31. Wolfgang Glänzel & Balázs Schlemmer & Bart Thijs, 2003. "Better late than never? On the chance to become highly cited only beyond the standard bibliometric time horizon," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 571-586, November.
    32. Ponomarev, Ilya V. & Williams, Duane E. & Hackett, Charles J. & Schnell, Joshua D. & Haak, Laurel L., 2014. "Predicting highly cited papers: A Method for Early Detection of Candidate Breakthroughs," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 49-55.
    33. 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.
    34. Jiang Li, 2014. "Citation curves of “all-elements-sleeping-beauties”: “flash in the pan” first and then “delayed recognition”," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 595-601, August.
    35. Chao Min & Ying Ding & Jiang Li & Yi Bu & Lei Pei & Jianjun Sun, 2018. "Innovation or imitation: The diffusion of citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(10), pages 1271-1282, October.
    36. Ehsan Mohammadi & Mike Thelwall, 2014. "Mendeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(8), pages 1627-1638, August.
    37. Hadas Shema & Judit Bar-Ilan & Mike Thelwall, 2014. "Do blog citations correlate with a higher number of future citations? Research blogs as a potential source for alternative metrics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 1018-1027, May.
    38. 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.
    39. Ehsan Mohammadi & Mike Thelwall & Stefanie Haustein & Vincent Larivière, 2015. "Who reads research articles? An altmetrics analysis of Mendeley user categories," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(9), pages 1832-1846, September.
    40. 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.
    41. Leydesdorff, Loet & Bornmann, Lutz & Marx, Werner & Milojević, Staša, 2014. "Referenced Publication Years Spectroscopy applied to iMetrics: Scientometrics, Journal of Informetrics, and a relevant subset of JASIST," Journal of Informetrics, Elsevier, vol. 8(1), pages 162-174.
    42. Ting Cong & Zhichao Fang & Rodrigo Costas, 2022. "WeChat uptake of chinese scholarly journals: an analysis of CSSCI-indexed journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7091-7110, December.
    43. Thed van Leeuwen & Robert Tijssen, 2000. "Interdisciplinary dynamics of modern science: analysis of cross-disciplinary citation flows," Research Evaluation, Oxford University Press, vol. 9(3), pages 183-187, December.
    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. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    2. Jianhua Hou & Xiucai Yang, 2019. "Patent sleeping beauties: evolutionary trajectories and identification methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 187-215, July.
    3. 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.
    4. 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.
    5. 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.
    6. Jianhua Hou & Hao Li & Yang Zhang, 2020. "Identifying the princes base on Altmetrics: An awakening mechanism of sleeping beauties from the perspective of social media," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-28, November.
    7. 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.
    8. 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.
    9. Jianhua Hou & Hao Li & Yang Zhang, 2023. "Altmetrics-based sleeping beauties: necessity or just a supplement?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5477-5506, October.
    10. Onodera, Natsuo, 2016. "Properties of an index of citation durability of an article," Journal of Informetrics, Elsevier, vol. 10(4), pages 981-1004.
    11. Yu Liu & Dan Lin & Xiujuan Xu & Shimin Shan & Quan Z. Sheng, 2018. "Multi-views on Nature Index of Chinese academic institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 823-837, March.
    12. Bornmann, Lutz, 2014. "Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics," Journal of Informetrics, Elsevier, vol. 8(4), pages 895-903.
    13. Jianhua Hou & Xiucai Yang & Haoyang Song & Haiyue Yao, 2023. "Will patent family be dormant? Research on the identification and characteristics of sleeping beauty’s patent family," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5361-5387, October.
    14. Maryam Moshtagh & Tahereh Jowkar & Maryam Yaghtin & Hajar Sotudeh, 2023. "The moderating effect of altmetrics on the correlations between single and multi-faceted university ranking systems: the case of THE and QS vs. Nature Index and Leiden," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 761-781, January.
    15. ZhangJian Zong & XuanZhen Liu & Hui Fang, 2018. "Sleeping beauties with no prince based on the co-citation criterion," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1841-1852, December.
    16. Hui Fang, 2018. "Analysing the variation tendencies of the numbers of yearly citations for sleeping beauties in science by using derivative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 1051-1070, May.
    17. 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.
    18. Jianhua Hou & Da Ma, 2020. "How the high-impact papers formed? A study using data from social media and citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2597-2615, December.
    19. Jianhua Hou, 2017. "Exploration into the evolution and historical roots of citation analysis by referenced publication year spectroscopy," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1437-1452, March.
    20. You Song & Fangling Situ & Hongjun Zhu & Jinzhi Lei, 2018. "To be the Prince to wake up Sleeping Beauty: the rediscovery of the delayed recognition studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 9-24, October.

    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:9:d:10.1007_s11192-023-04785-4. 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.