Altmetrics, webometrics and informetrics as the complementary vectors in the modern bibliometrics is a research paper published in Scientific and Technical Libraries (2019). On theSindex it has a DataRank of 0.404. It has been cited 6 times, with 6 citing works in its 1-hop citation network.
Modern practical experience in bibliometrics is based on the scrupulous study of researchers’ performance on the Internet. Most of the Russian scientists are confused by an array of indicators, and are unable to assess their own level of influence on modern science. The dynamic and successful development of science and related scientific and research activities throughout the twentieth century has revealed the vital problem of measuring the effects (impacts) of research findings. Participating in the academic life, the researchers have to evaluate constantly themselves and the colleagues in terms of assessing individual and collective contribution and using "digital" scientometrical indicators. The author reviews the modern perception of the significance and role of "digital" indicators in scientometrics on the whole, and in bibliometrics, in particular, in assessing modern science and its findings. While such indicators as Hirsch index, impact factor of scientific publications are the widely-known indicators, and Eigenfactor (native factor) is familiar to the few, almost no one knows what altmetrics and informetrics are and how to apply them. This article will make the first work in the series on the practical aspects of applying "digital" bibliometrical indicators in the daily researcher’s routine.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.292
From this paper's citation signal
Citation Network Contribution
0.113
From 4 citing papers with measurable signal
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 72% comes from its base citations and 28% from the citation network (4 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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