The Google Scholar Experiment: how to index false papers and manipulate bibliometric indicators

TL;DR

This study demonstrates how easily false papers can manipulate Google Scholar's citation metrics, raising concerns about the reliability and transparency of bibliometric indicators derived from it.

Contribution

The paper presents an experiment showing Google Scholar's vulnerability to citation manipulation through false papers, highlighting potential impacts on bibliometric assessments.

Findings

Google Scholar failed to detect the false papers' citation outburst

Manipulation significantly inflated authors' citation counts

Potential impact on journal-level metrics and research evaluation

Abstract

Google Scholar has been well received by the research community. Its promises of free, universal and easy access to scientific literature as well as the perception that it covers better than other traditional multidisciplinary databases the areas of the Social Sciences and the Humanities have contributed to the quick expansion of Google Scholar Citations and Google Scholar Metrics: two new bibliometric products that offer citation data at the individual level and at journal level. In this paper we show the results of a experiment undertaken to analyze Google Scholar's capacity to detect citation counting manipulation. For this, six documents were uploaded to an institutional web domain authored by a false researcher and referencing all the publications of the members of the EC3 research group at the University of Granada. The detection of Google Scholar of these papers outburst the citations included in the Google Scholar Citations profiles of the authors. We discuss the effects of such outburst and how it could affect the future development of such products not only at individual level but also at journal level, especially if Google Scholar persists with its lack of transparency.