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Posted, visited, exported: Altmetrics in the social tagging system BibSonomy

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  • Zoller, Daniel
  • Doerfel, Stephan
  • Jäschke, Robert
  • Stumme, Gerd
  • Hotho, Andreas

Abstract

In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.

Suggested Citation

  • Zoller, Daniel & Doerfel, Stephan & Jäschke, Robert & Stumme, Gerd & Hotho, Andreas, 2016. "Posted, visited, exported: Altmetrics in the social tagging system BibSonomy," Journal of Informetrics, Elsevier, vol. 10(3), pages 732-749.
    • Handle: RePEc:eee:infome:v:10:y:2016:i:3:p:732-749
    DOI: 10.1016/j.joi.2016.03.005
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    References listed on IDEAS

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    2. Akella, Akhil Pandey & Alhoori, Hamed & Kondamudi, Pavan Ravikanth & Freeman, Cole & Zhou, Haiming, 2021. "Early indicators of scientific impact: Predicting citations with altmetrics," Journal of Informetrics, Elsevier, vol. 15(2).
    3. Mike Thelwall, 2018. "Differences between journals and years in the proportions of students, researchers and faculty registering Mendeley articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 717-729, May.
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    5. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.

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