2,064 research outputs found
Utilising content marketing metrics and social networks for academic visibility
There are numerous assumptions on research evaluation in terms of quality and relevance of academic contributions. Researchers are becoming increasingly acquainted with bibliometric indicators, including; citation analysis, impact factor, h-index, webometrics and academic social networking sites. In this light, this chapter presents a review of these concepts as it considers relevant theoretical underpinnings that are related to the content marketing of scholars. Therefore, this contribution critically evaluates previous papers that revolve on the subject of academic reputation as it deliberates on the individual researchers’ personal branding. It also explains how metrics are currently being used to rank the academic standing of journals as well as higher educational institutions. In a nutshell, this chapter implies that the scholarly impact depends on a number of factors including accessibility of publications, peer review of academic work as well as social networking among scholars.peer-reviewe
Impact Factor: outdated artefact or stepping-stone to journal certification?
A review of Garfield's journal impact factor and its specific implementation
as the Thomson Reuters Impact Factor reveals several weaknesses in this
commonly-used indicator of journal standing. Key limitations include the
mismatch between citing and cited documents, the deceptive display of three
decimals that belies the real precision, and the absence of confidence
intervals. These are minor issues that are easily amended and should be
corrected, but more substantive improvements are needed. There are indications
that the scientific community seeks and needs better certification of journal
procedures to improve the quality of published science. Comprehensive
certification of editorial and review procedures could help ensure adequate
procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table
Applying Science Models for Search
The paper proposes three different kinds of science models as value-added
services that are integrated in the retrieval process to enhance retrieval
quality. The paper discusses the approaches Search Term Recommendation,
Bradfordizing and Author Centrality on a general level and addresses
implementation issues of the models within a real-life retrieval environment.Comment: 14 pages, 3 figures, ISI 201
A review of the characteristics of 108 author-level bibliometric indicators
An increasing demand for bibliometric assessment of individuals has led to a
growth of new bibliometric indicators as well as new variants or combinations
of established ones. The aim of this review is to contribute with objective
facts about the usefulness of bibliometric indicators of the effects of
publication activity at the individual level. This paper reviews 108 indicators
that can potentially be used to measure performance on the individual author
level, and examines the complexity of their calculations in relation to what
they are supposed to reflect and ease of end-user application.Comment: to be published in Scientometrics, 201
Ranking forestry journals using the h-index
An expert ranking of forestry journals was compared with journal impact
factors and h-indices computed from the ISI Web of Science and internet-based
data. Citations reported by Google Scholar appear to offer the most efficient
way to rank all journals objectively, in a manner consistent with other
indicators. This h-index exhibited a high correlation with the journal impact
factor (r=0.92), but is not confined to journals selected by any particular
commercial provider. A ranking of 180 forestry journals is presented, on the
basis of this index.Comment: 21 pages, 3 figures, 5 tables. New table added in response to
reviewer comment
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