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Measuring social media activity of scientific literature: an exhaustive comparison of scopus and novel altmetrics big data

Author

Listed:
  • Saeed-Ul Hassan

    (Information Technology University)

  • Mubashir Imran

    (Information Technology University)

  • Uzair Gillani

    (Information Technology University)

  • Naif Radi Aljohani

    (King Abdulaziz University)

  • Timothy D. Bowman

    (Wayne State University)

  • Fereshteh Didegah

    (Simon Fraser University)

Abstract

This paper measures social media activities of 15 broad scientific disciplines indexed in Scopus database using Altmetric.com data. First, the presence of Altmetric.com data in Scopus database is investigated, overall and across disciplines. Second, a zero-truncated negative binomial model is used to determine the association of various factors with increasing or decreasing citations. Lastly, the effectiveness of altmetric indices to identify publications with high citation impact is comprehensively evaluated by deploying area under the curve (AUC)—an application of receiver operating characteristic. Results indicate a rapid increase in the presence of Altmetric.com data in Scopus database from 10.19% in 2011 to 20.46% in 2015. It was found that Blog count was the most important factor in the field of Health Professions and Nursing as it increased the number of citations by 38.6%, followed by Twitter count increasing the number of citations by 8% in the field of Physics and Astronomy. The results of receiver operating characteristic show that altmetric indices can be a good indicator to discriminate highly cited publications, with an encouragingly AUC = 0.725 between highly cited publications and total altmetric count. Overall, findings suggest that altmetrics can be used to distinguish highly cited publications. The implications of this research are significant in many different directions. Firstly, they set the basis for a further investigation of altmetrics efficiency to predict publications impact and most significantly promote new insights for the measurement of research outcome dissemination over social media.

Suggested Citation

  • Saeed-Ul Hassan & Mubashir Imran & Uzair Gillani & Naif Radi Aljohani & Timothy D. Bowman & Fereshteh Didegah, 2017. "Measuring social media activity of scientific literature: an exhaustive comparison of scopus and novel altmetrics big data," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1037-1057, November.
    • Handle: RePEc:spr:scient:v:113:y:2017:i:2:d:10.1007_s11192-017-2512-x
    DOI: 10.1007/s11192-017-2512-x
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    17. Ortega, José Luis, 2020. "Proposal of composed altmetric indicators based on prevalence and impact dimensions," Journal of Informetrics, Elsevier, vol. 14(4).
    18. Jyoti Paswan & Vivek Kumar Singh & Mousumi Karmakar & Prashasti Singh, 2022. "Does university–industry–government collaboration in research gets higher citation and altmetric impact? A case study from India," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6063-6082, November.
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    20. 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.
    21. Iraklis Varlamis & Dimitrios Michail & Foteini Glykou & Panagiotis Tsantilas, 2022. "A Survey on the Use of Graph Convolutional Networks for Combating Fake News," Future Internet, MDPI, vol. 14(3), pages 1-19, February.
    22. Dorte Drongstrup & Shafaq Malik & Naif Radi Aljohani & Salem Alelyani & Iqra Safder & Saeed-Ul Hassan, 2020. "Can social media usage of scientific literature predict journal indices of AJG, SNIP and JCR? An altmetric study of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1541-1558, November.
    23. Xi Zhang & Xianhai Wang & Hongke Zhao & Patricia Ordóñez de Pablos & Yongqiang Sun & Hui Xiong, 2019. "An effectiveness analysis of altmetrics indices for different levels of artificial intelligence publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1311-1344, June.
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