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Tracking the digital footprints to scholarly articles from social media

Author

Listed:
  • Xianwen Wang

    (Dalian University of Technology)

  • Zhichao Fang

    (Dalian University of Technology)

  • Xinhui Guo

    (Dalian University of Technology)

Abstract

Scholarly articles are discussed and shared on social media, which generates altmetrics. On the opposite side, what is the impact of social media on the dissemination of scholarly articles and how to measure it? What are the visiting patterns? Investigating these issues, the purpose of this study is to seek a solution to fill the research gap, specifically, to explore the dynamic visiting patterns directed by social media, and examine the effects of social buzz on the article visits. Using the unique real referral data of 110 scholarly articles, which are daily updated in a 90-day period, this paper proposes a novel method to make analysis. We find that visits from social media are fast to accumulate but decay rapidly. Twitter and Facebook are the two most important social referrals that directing people to scholarly articles, the two are about the same and account for over 95 % of the total social referral directed visits. There is synchronism between tweets and tweets resulted visits. Social media and open access are playing important roles in disseminating scholarly articles and promoting public understanding science, which are confirmed quantitatively for the first time with real data in this study.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:2:d:10.1007_s11192-016-2086-z
    DOI: 10.1007/s11192-016-2086-z
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    References listed on IDEAS

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    Cited by:

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    3. Zhichao Fang & Rodrigo Costas, 2020. "Studying the accumulation velocity of altmetric data tracked by Altmetric.com," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1077-1101, May.
    4. Liwei Zhang & Jue Wang, 2021. "What affects publications’ popularity on Twitter?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9185-9198, November.
    5. 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.
    6. 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.
    7. 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.
    8. Jingda Ding & Dehui Du, 2023. "A study of the correlation between publication delays and measurement indicators of journal articles in the social network environment—based on online data in PLOS," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1711-1743, March.
    9. Li, Huixu & Liu, Lanjian & Wang, Xianwen, 2021. "The open access effect in social media exposure of scholarly articles: A matched-pair analysis," Journal of Informetrics, Elsevier, vol. 15(3).
    10. 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).

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