| Title |
Normalizing Google Scholar data for use in research evaluation
|
|---|---|
| Published in |
Scientometrics, May 2017
|
| DOI | 10.1007/s11192-017-2415-x |
| Pubmed ID | |
| Authors |
John Mingers, Martin Meyer |
| Abstract |
Using bibliometric data for the evaluation of the research of institutions and individuals is becoming increasingly common. Bibliometric evaluations across disciplines require that the data be normalized to the field because the fields are very different in their citation processes. Generally, the major bibliographic databases such as Web of Science (WoS) and Scopus are used for this but they have the disadvantage of limited coverage in the social science and humanities. Coverage in Google Scholar (GS) is much better but GS has less reliable data and fewer bibliometric tools. This paper tests a method for GS normalization developed by Bornmann et al. (J Assoc Inf Sci Technol 67:2778-2789, 2016) on an alternative set of data involving journal papers, book chapters and conference papers. The results show that GS normalization is possible although at the moment it requires extensive manual involvement in generating and validating the data. A comparison of the normalized results for journal papers with WoS data shows a high degree of convergent validity. |
X Demographics
The data shown below were collected from the profiles of 57 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 11 | 19% |
| France | 3 | 5% |
| India | 2 | 4% |
| Chile | 2 | 4% |
| United Kingdom | 2 | 4% |
| United States | 2 | 4% |
| South Africa | 1 | 2% |
| Australia | 1 | 2% |
| Ireland | 1 | 2% |
| Other | 8 | 14% |
| Unknown | 24 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 38 | 67% |
| Scientists | 13 | 23% |
| Science communicators (journalists, bloggers, editors) | 4 | 7% |
| Practitioners (doctors, other healthcare professionals) | 2 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 1 | 1% |
| Unknown | 97 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 15% |
| Librarian | 14 | 14% |
| Student > Ph. D. Student | 14 | 14% |
| Other | 8 | 8% |
| Student > Master | 7 | 7% |
| Other | 22 | 22% |
| Unknown | 18 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 26 | 27% |
| Computer Science | 11 | 11% |
| Arts and Humanities | 7 | 7% |
| Agricultural and Biological Sciences | 5 | 5% |
| Economics, Econometrics and Finance | 4 | 4% |
| Other | 26 | 27% |
| Unknown | 19 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 37. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 November 2020.
All research outputs
#1,078,691
of 25,016,456 outputs
Outputs from Scientometrics
#150
of 2,872 outputs
Outputs of similar age
#21,578
of 319,252 outputs
Outputs of similar age from Scientometrics
#4
of 54 outputs
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We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.