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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
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    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. 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).
    3. 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).
    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 American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(2), pages 329-339, February.
    5. 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.
    6. 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.
    7. Lachance, Christian & Larivière, Vincent, 2014. "On the citation lifecycle of papers with delayed recognition," Journal of Informetrics, Elsevier, vol. 8(4), pages 863-872.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Jianhua Hou & Xiucai Yang, 2019. "Patent sleeping beauties: evolutionary trajectories and identification methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 187-215, July.
    22. 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.
    23. Trueman, Brett, 1994. "Analyst Forecasts and Herding Behavior," The Review of Financial Studies, Society for Financial Studies, vol. 7(1), pages 97-124.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. Stoneman, Paul & Diederen, Paul, 1994. "Technology Diffusion and Public Policy," Economic Journal, Royal Economic Society, vol. 104(425), pages 918-930, July.
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