The dispersion of the citation distribution of top scientists’ publications

Abramo, Giovanni; D’Angelo, Ciriaco Andrea; Soldatenkova, Anastasiia

doi:10.1007/s11192-016-2143-7

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…In effect, if researchers only used, say, Google Scholar and Mendeley Suggest to discover relevant publications, they would probably reproduce bibliometric redundancy – as is visible in the standard assumption of a Pareto distribution in bibliometrics, according to which 80% of all citations go to just 20% of all research outputs ([59–61]; but note that there is evidence of a gradual change in this pattern, cf. [62]).…”

Section: Discussionmentioning

confidence: 99%

A typology of research discovery tools

Nishikawa-Pacher

2021

Journal of Information Science

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There has been a proliferation of new research discovery tools that aid scientists in finding relevant publications. To obtain a general overview of this development, this article generates a conceptual typology of all possible research discovery tools by drawing from the information-theoretical concepts of redundancy/variety. Bibliometric links between scholarly publications can thus exhibit ‘redundancy’ (i.e. expectable linkages between academic works) or ‘variety’ (i.e. original co-occurrence patterns). On the redundancy-reproducing end of the typology are machines that harness extant co-citations or keyword queries, such as academic search engines and paper recommender systems. The variety end of the spectrum harbours services that enable categorial browsing or that suggest publications randomly, such as journals’ tables of contents or random paper bots. The typology has implications for understanding how the design of research discovery platforms may ultimately shape aggregate citational networks of science.

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Section: Discussionmentioning

confidence: 99%

A typology of research discovery tools

Nishikawa-Pacher

2021

Journal of Information Science

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“…never cited, and even if they are, it usually takes a year or more before they receive their first citation (Golosovsky, 2017;Abramo et al, 2016). Consequently, CPA has a low coverage, i.e.…”

Section: Introductionmentioning

confidence: 99%

Virtual Citation Proximity (VCP): Learning a Hypothetical In-Text Citation-Proximity Metric For Uncited Documents

Molloy¹,

Beel²,

Aizawa³

2020

Preprint

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The relatedness of research articles, patents, court rulings, webpages, and other document types is often calculated with citation or hyperlink-based approaches like co-citation (proximity) analysis. The main limitation of citation-based approaches is that they cannot be used for documents that receive little or no citations. We propose Virtual Citation Proximity (VCP), a Siamese Neural Network architecture, which combines the advantages of co-citation proximity analysis (diverse notions of relatedness / high recommendation performance), with the advantage of content-based filtering (high coverage). VCP is trained on a corpus of documents with textual features, and with real citation proximity as ground truth. VCP then predicts for any two documents, based on their title and abstract, in what proximity the two documents would be co-cited, if they were indeed co-cited. The prediction can be used in the same way as real citation proximity to calculate document relatedness, even for uncited documents. In our evaluation with 2 million co-citations from Wikipedia articles, VCP achieves an MAE of 0.0055, i.e. an improvement of 20% over the baseline, though the learning curve suggests that more work is needed.

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“…There is now a very extensive literature on the theory and practice of citation analysis. The distribution of citation scores has been the subject of extensive research, much of it mathematical (van Raan 2001;Anastadiadis et al 2010;Ruiz-Castillo 2013;Abramo et al 2016). It has also been established that the citations to groups of papers, which must strictly be counted in a fixed time window, vary with the parameters of the papers such as the numbers of authors, the numbers of addresses, the numbers of funding acknowledgments, the field of study, and whether the paper is applied (clinical for biomedical research) or basic (Lewison and Dawson 1998;Roe et al 2010;van Eck et al 2013).…”

Section: Introductionmentioning

confidence: 99%

A new database of the references on international clinical practice guidelines: a facility for the evaluation of clinical research

Eriksson¹,

Billhult

Billhult³

et al. 2019

Scientometrics

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Although there are now several bibliographic databases of research publications, such as Google Scholar, Pubmed, Scopus, and the Web of Science (WoS), and some also include counts of citations, there is at present no similarly comprehensive database of the rapidly growing number of clinical practice guidelines (CPGs), with their references, which sometimes number in the hundreds. CPGs have been shown to be useful for the evaluation of clinical (as opposed to basic) biomedical research, which often suffers from relatively low counts of citations in the serial literature. The objectives were to introduce a new citation database, clinical impact ® , and demonstrate how it can be used to evaluate research impact of clinical research publications by exploring the characteristics of CPG citations of two sets of papers, as well as show temporal variation of clinical impact ® and the WoS. The paper includes the methodology used to retain the data and also the rationale adopted to achieve data quality. The analysis showed that although CPGs tend preferentially to cite papers from their own country, this is not always the case. It also showed that cited papers tend to have a more clinical research level than uncited papers. An analysis of diachronous citations in both clinical impact ® and the WoS showed that although the WoS citations showed a decreasing trend after a peak at 2-3 years after publication, this was less clear for CPG citations and a longer timescale would be needed to evaluate their impact on these documents.

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The dispersion of the citation distribution of top scientists’ publications

Cited by 7 publications

References 15 publications

A typology of research discovery tools

A typology of research discovery tools

Virtual Citation Proximity (VCP): Learning a Hypothetical In-Text Citation-Proximity Metric For Uncited Documents

A new database of the references on international clinical practice guidelines: a facility for the evaluation of clinical research

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