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Detecting h-index manipulation through self-citation analysis

Christoph Bartneck, +1 more
- 01 Apr 2011 - 
- Vol. 87, Iss: 1, pp 85-98
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TLDR
The q-index is proposed as an indicator for how strategically an author has placed self-citations, and which serves as a tool to detect possible manipulation of the h-index.
Abstract
The h-index has received an enormous attention for being an indicator that measures the quality of researchers and organizations. We investigate to what degree authors can inflate their h-index through strategic self-citations with the help of a simulation. We extended Burrell's publication model with a procedure for placing self-citations, following three different strategies: random self-citation, recent self-citations and h-manipulating self-citations. The results show that authors can considerably inflate their h-index through self-citations. We propose the q-index as an indicator for how strategically an author has placed self-citations, and which serves as a tool to detect possible manipulation of the h-index. The results also show that the best strategy for an high h-index is publishing papers that are highly cited by others. The productivity has also a positive effect on the h-index.

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Citations
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The natural selection of bad science.

TL;DR: In this paper, the authors present a 60-year meta-analysis of statistical power in the behavioural sciences and show that power has not improved despite repeated demonstrations of the necessity of increasing power.
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The Natural Selection of Bad Science

TL;DR: A 60-year meta-analysis of statistical power in the behavioural sciences is presented and it is shown that power has not improved despite repeated demonstrations of the necessity of increasing power, and that replication slows but does not stop the process of methodological deterioration.
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Academic research in the 21st century: maintaining scientific integrity in a climate of perverse incentives and hypercompetition.

TL;DR: Acemia and federal agencies should better support science as a public good, and incentivize altruistic and ethical outcomes, while de-emphasizing output.
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Using publication metrics to highlight academic productivity and research impact.

TL;DR: This article provides a broad overview of widely available measures of academic productivity and impact using publication data and highlights uses of these metrics for various purposes.
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The Google scholar experiment: How to index false papers and manipulate bibliometric indicators

TL;DR: In this paper, the Journal of the American Society for Information Science and Technology (ASIS) has published a paper on the use of data mining techniques in information science and technology.
References
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Journal ArticleDOI

An index to quantify an individual's scientific research output

TL;DR: The index h, defined as the number of papers with citation number ≥h, is proposed as a useful index to characterize the scientific output of a researcher.
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Theory and practise of the g-index

TL;DR: It is shown that the g-index inherits all the good properties of the h-index and better takes into account the citation scores of the top articles and yields a better distinction between and order of the scientists from the point of view of visibility.
Journal IssueDOI

Impact of data sources on citation counts and rankings of LIS faculty: Web of science versus scopus and google scholar

TL;DR: Results show that Scopus significantly alters the relative ranking of those scholars that appear in the middle of the rankings and that GS stands out in its coverage of conference proceedings as well as international, non-English language journals.
Journal ArticleDOI

The skewness of science

TL;DR: The skewness in the citedness distribution of each author's articles, the large overlap between different authors and the existence of field‐dependent systematic differences in citedness would seem to make even article citations unsuitable for evaluation of individual scientists or research groups.
Journal ArticleDOI

A macro study of self-citation

Dag W. Aksnes
- 01 Feb 2003 - 
TL;DR: This study investigates the role of self-citation in the scientific production of Norway (1981-1996) and finds that 36% of all citations represent author self-Citations, however, this percentage is decreasing when citations are traced for longer periods.