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Tracking the digital footprints to scholarly articles from social media

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.

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Acknowledgments

The work was supported by the project of “National Natural Science Foundation of China” (61301227), the project of “the Fundamental Research Funds for the Central Universities”(DUT15YQ111), “Liaoning Province Higher Education Innovation Team Fund” (WT2015002), and “Humanity and Social Science Foundation of Ministry of Education of China” (11YJA630128).

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Correspondence to Xianwen Wang.

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Wang, X., Fang, Z. & Guo, X. Tracking the digital footprints to scholarly articles from social media. Scientometrics 109, 1365–1376 (2016). https://doi.org/10.1007/s11192-016-2086-z

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  • DOI: https://doi.org/10.1007/s11192-016-2086-z

Keywords

  • Altmetrics
  • Social media
  • Twitter
  • Facebook
  • PeerJ
  • Public understanding science