Abstract
With a rapidly increasing corpus of published papers, assessing their scientific impact has become increasingly challenging. Particularly, for analysts performing systematic literature analysis, such as a systematic literature review or systematic mapping study, the problem of manually assessing a large data set has now become quite evident. Thus, the research community is actively involved in developing techniques relying on different methods to determine impact of a paper with reduced manual effort, for example, using bibliometrics, and the more recently introduced, altmetrics. Therefore, in this work we extend the ongoing investigation and propose weighted altmetric scores for a more fair and reliable analysis of papers, eventually supporting the literature analysis process. Our findings show that weighted altmetrics perform well and achieve an accuracy of 69.81% considerably reducing the time and effort required for a manual literature analysis.
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Complete dataset is available here: https://doi.org/10.5281/zenodo.6905592.
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Acknowledgements
This research is funded by the German DFG-MatWerk, NFDI 38/1, project # 460247524 and supported by the Helmholtz Metadata Collaboration Platform & the German National Research Data Infrastructure.
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Shakeel, Y., Bharti, A., Leich, T., Saake, G. (2022). Weighted Altmetric Scores to Facilitate Literature Analyses. In: Silvello, G., et al. Linking Theory and Practice of Digital Libraries. TPDL 2022. Lecture Notes in Computer Science, vol 13541. Springer, Cham. https://doi.org/10.1007/978-3-031-16802-4_46
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