Scientometrics

, Volume 109, Issue 2, pp 1365–1376

Tracking the digital footprints to scholarly articles from social media

Article

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.

Keywords

Altmetrics Social media Twitter Facebook PeerJ Public understanding science 

References

  1. Allen, H. G., Stanton, T. R., Di Pietro, F., & Moseley, G. L. (2013). Social media release increases dissemination of original articles in the clinical pain sciences. PLoS ONE, 8(7), e68914.CrossRefGoogle Scholar
  2. Bornmann, L. (2014a). Alternative metrics in scientometrics: A meta-analysis of research into three altmetrics. Scientometrics, 103(3), 1123–1144.CrossRefGoogle Scholar
  3. Bornmann, L. (2014b). Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics. Journal of Informetrics, 8(4), 895–903.CrossRefGoogle Scholar
  4. Bornmann, L., & Haunschild, R. (2015). Which people use which scientific papers? An evaluation of data from F1000 and Mendeley. Journal of Informetrics, 9(3), 477–487.CrossRefGoogle Scholar
  5. Cheung, M. K. (2013). Altmetrics: Too soon for use in assessment. Nature, 494(7436), 176.CrossRefGoogle Scholar
  6. Costas, R., Zahedi, Z., & Wouters, P. (2014). Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. Journal of the Association for Information Science and Technology, 66(10), 2003–2019.CrossRefGoogle Scholar
  7. Dinsmore, A., Allen, L., & Dolby, K. (2014). Alternative perspectives on impact: The potential of ALMs and altmetrics to inform funders about research impact. PLoS Biology, 12(11), e1002003.CrossRefGoogle Scholar
  8. Eysenbach, G. (2011). Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact. Journal of Medical Internet Research, 13(4), e123.CrossRefGoogle Scholar
  9. Glänzel, W., & Gorraiz, J. (2015). Usage metrics versus altmetrics: Confusing terminology? Scientometrics, 102(3), 2161–2164.CrossRefGoogle Scholar
  10. Haustein, S., Peters, I., Bar-Ilan, J., Priem, J., Shema, H., & Terliesner, J. (2013). Coverage and adoption of altmetrics sources in the bibliometric community. Scientometrics, 101(2), 1145–1163.CrossRefGoogle Scholar
  11. Mohammadi, E., Thelwall, M., Haustein, S., & Larivière, V. (2015). Who reads research articles? An altmetrics analysis of Mendeley user categories. Journal of the American Society for Information Science and Technology, 66(9), 1832–1846.CrossRefGoogle Scholar
  12. Priem, J., & Hemminger, B. H. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday, 15(7), 16.CrossRefGoogle Scholar
  13. Priem, J., Taraborelli, D., Groth, P., & Neylon, C. (2010). Altmetrics: A manifesto. 1 May, 2016. Retrieved from http://altmetrics.org/manifesto/.
  14. Sotudeh, H., Mazarei, Z., & Mirzabeigi, M. (2015). CiteULike bookmarks are correlated to citations at journal and author levels in library and information science. Scientometrics, 105(3), 2237–2248.CrossRefGoogle Scholar
  15. Thelwall, M., Haustein, S., Larivière, V., & Sugimoto, C. R. (2013). Do altmetrics work? Twitter and ten other social web services. PLoS ONE, 8(5), e64841.CrossRefGoogle Scholar
  16. Thelwall, M., Kousha, K., Dinsmore, A., & Dolby, K. (2016). Alternative metric indicators for funding scheme evaluations. Aslib Journal of Information Management, 68(1), 2–18.CrossRefGoogle Scholar
  17. Torres-Salinas, D., Cabezas-Clavijo, A., & Jimenez-Contreras, E. (2013). Altmetrics: New indicators for scientific communication in web 20. Comunicar, 41(41), 53–60.CrossRefGoogle Scholar
  18. Wang, X., Liu, C., Mao, W., & Fang, Z. (2015). The open access advantage considering citation, article usage and social media attention. Scientometrics, 103(2), 555–564.CrossRefGoogle Scholar
  19. Wang, X., Mao, W., Xu, S., & Zhang, C. (2014). Usage history of scientific literature: Nature metrics and metrics of Nature publications. Scientometrics, 98(3), 1923–1933.CrossRefGoogle Scholar
  20. Wang, X., Xu, S., & Fang, Z. (2016). Tracing digital footprints to academic articles: An investigation of PeerJ publication referral data. arXiv:1205.5611.

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2016

Authors and Affiliations

  1. 1.WISE Lab, Faculty of Humanities and Social SciencesDalian University of TechnologyDalianChina

Personalised recommendations