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Manipulating Google Scholar Citations and Google Scholar Metrics: simple, easy and tempting

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TLDR
An experiment is presented in which the Google Citations profiles of a research group are manipulated through the creation of false documents that cite their documents, and consequently, the journals in which they have published modifying their H index.
Abstract
The launch of Google Scholar Citations and Google Scholar Metrics may provoke a revolution in the research evaluation field as it places within every researchers reach tools that allow bibliometric measuring. In order to alert the research community over how easily one can manipulate the data and bibliometric indicators offered by Google s products we present an experiment in which we manipulate the Google Citations profiles of a research group through the creation of false documents that cite their documents, and consequently, the journals in which they have published modifying their H index. For this purpose we created six documents authored by a faked author and we uploaded them to a researcher s personal website under the University of Granadas domain. The result of the experiment meant an increase of 774 citations in 129 papers (six citations per paper) increasing the authors and journals H index. We analyse the malicious effect this type of practices can cause to Google Scholar Citations and Google Scholar Metrics. Finally, we conclude with several deliberations over the effects these malpractices may have and the lack of control tools these tools offer

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The number that's devouring science

TL;DR: The Faculty Research & Books Government & Politics Money & Management Information Technology Students Athletics International Community Colleges Short Subjects Gazette Corrections Opinion & Forums Careers Sponsored information & solutions Chronicle/Gartner Leadership Forum Services Help Contact us Subscribe Manage your account Advertise with us Rights & permissions From the issue dated October 14, 2005
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Is Google Scholar useful for bibliometrics? A webometric analysis

TL;DR: A novel approach is introduced to check the usefulness of this database for bibliometric analysis, and especially research evaluation, instead of names of authors or institutions, a webometric analysis of academic web domains is performed.
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Detecting h-index manipulation through self-citation analysis

TL;DR: 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.

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