Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus
Abstract
:1. Introduction
2. Related Studies
- -
- -
- -
- -
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- Documents with many citations received have more readers and more citations and, in this way, consolidate their top position [61].
3. Methodology
“Google Scholar aims to rank documents the way researchers do, weighing the full text of each document, where it was published, who it was written by as well as how often and how recently it has been cited in other scholarly literature.”[71].
“In a nutshell, we use the dynamic eigencentrality measure of the heterogeneous MAG to determine the ranking of publications. The framework ensures that a publication will be ranked high if it impacts highly ranked publications, is authored by highly ranked scholars from prestigious institutions, or is published in a highly regarded venue in highly competitive fields. Mathematically speaking, the eigencentrality measure can be viewed as the likelihood that a publication will be mentioned as highly impactful when a survey is posed to the entire scholarly community”[76]
4. Analysis of Results
5. Discussion
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A. List of Terms Used in The Searches
Search Words | Rho Google Scholar Title | Rho Google Scholar Not Title | Rho Microsoft Academic Title |
---|---|---|---|
Median | 0.990 ** | 0.968 ** | 0.907 ** |
approach | 0.742 ** | 0.700 ** | 0.548 ** |
assessment | 0.632 ** | 0.563 ** | 0.545 ** |
authority | 0.868 ** | 0.815 ** | 0.465 ** |
consistent | 0.956 ** | 0.783 ** | 0.596 ** |
context | 0.851 ** | 0.681 ** | 0.483 ** |
data | 0.645 ** | 0.662 ** | 0.601 ** |
definition | 0.907 ** | 0.783 ** | 0.636 ** |
derived | 0.905 ** | 0.682 ** | 0.568 ** |
distribution | 0.781 ** | 0.649 ** | 0.458 ** |
estimate | 0.939 ** | 0.813 ** | 0.527 ** |
evidence | 0.761 ** | 0.616 ** | 0.488 ** |
fact | 0.899 ** | 0.229 ** | 0.517 ** |
factor | 0.490 ** | 0.591 ** | 0.490 ** |
formula | 0.872 ** | 0.773 ** | 0.352 ** |
function | 0.789 ** | 0.650 ** | 0.529 ** |
interpretation | 0.852 ** | 0.723 ** | 0.570 ** |
method | 0.762 ** | 0.665 ** | 0.613 ** |
percent | 0.932 ** | 0.861 ** | 0.478 ** |
principle | 0.879 ** | 0.812 ** | 0.530 ** |
research | 0.500 ** | 0.642 ** | 0.521 ** |
response | 0.741 ** | 0.603 ** | 0.500 ** |
significant | 0.929 ** | 0.709 ** | 0.557 ** |
source | 0.848 ** | 0.735 ** | 0.546 ** |
theory | 0.488 ** | 0.544 ** | 0.483 ** |
variable | 0.888 ** | 0.727 ** | 0.569 ** |
Search Words | Rho GS Title | Rho GS Not Title | Rho MA Title | Rho Scopus | Rho WoS Version 1 | Rho WoS Version 2 |
---|---|---|---|---|---|---|
Median | 0.994 ** | 0.721 ** | 0.937 ** | −0.107 ** | −0.075* | 0.907 ** |
approaches management | 0.391 ** | 0.447 ** | 0.587 ** | −0.004 | −0.102 ** | 0.581 ** |
area network | 0.871 ** | 0.108 ** | 0.462 ** | 0.025 | −0.054 | 0.610 ** |
assessment learning | 0.960 ** | 0.646 ** | 0.683 ** | 0.009 | −0.038 | 0.605 ** |
assessment tool | 0.855 ** | 0.476 ** | 0.619 ** | −0.006 | 0.058 | 0.556 ** |
benefit cost | 0.602 ** | 0.467 ** | 0.490 ** | −0.048 | −0.008 | 0.522 ** |
context awareness | 0.918 ** | 0.302 ** | 0.752 ** | −0.066* | −0.056 | 0.580 ** |
context model | 0.956 ** | −0.003 | 0.616 ** | −0.042 | 0.023 | 0.624 ** |
data mining | 0.875 ** | 0.818 ** | 0.747 ** | 0.072* | 0.009 | 0.654 ** |
distribution function | 0.868 ** | 0.171 ** | 0.415 ** | −0.051 | −0.069* | 0.520 ** |
environment engineering | 0.869 ** | 0.869 ** | 0.539 ** | −0.037 | −0.032 | 0.647 ** |
environment impact | 0.842 ** | 0.120 ** | 0.559 ** | −0.026 | −0.065* | 0.605 ** |
evidence practice | 0.968 ** | 0.206 ** | 0.712 ** | 0.021 | 0.005 | 0.517 ** |
function approximation | 0.903 ** | 0.162 ** | 0.619 ** | 0.053 | −0.036 | 0.646 ** |
period time | 0.956 ** | 0.027 | 0.525 ** | −0.102 ** | 0.036 | 0.554 ** |
probability distribution | 0.913 ** | −0.006 | 0.522 ** | −0.077* | −0.055 | 0.683 ** |
research design | 0.658 ** | 0.213 ** | 0.648 ** | 0.099 ** | 0.063* | 0.572 ** |
response rate | 0.881 ** | 0.176 ** | 0.522 ** | −0.035 | 0.114 ** | 0.606 ** |
response time | 0.851 ** | −0.072* | 0.469 ** | −0.016 | −0.043 | 0.543 ** |
source code | 0.887 ** | 0.082 ** | 0.631 ** | −0.119 ** | 0.043 | 0.621 ** |
source separation | 0.939 ** | 0.466 ** | 0.734 ** | 0.053 | −0.062 | 0.588 ** |
statistical theory | 0.772 ** | 0.203 ** | 0.573 ** | −0.085 ** | −0.081* | 0.657 ** |
structure factor | 0.821 ** | 0.334 ** | 0.575 ** | −0.209 ** | −0.026 | 0.607 ** |
structure function | 0.804 ** | −0.01 | 0.582 ** | −0.208 ** | −0.104 ** | 0.613 ** |
theory mind | 0.962 ** | 0.838 ** | 0.680 ** | −0.048 | 0.181 ** | 0.672 ** |
variable number | 0.958 ** | −0.120 ** | 0.656 ** | 0.072* | −0.001 | 0.081* |
Appendix B. Data Files
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Type | SEO/ASEO factor | Google Search | Google Scholar | Microsoft Academic | WoS | Scopus |
---|---|---|---|---|---|---|
On-page factors | Keywords in title | Yes [16,17,18,19,28,29,30] | Yes [31,32] | ? | Yes [40] | Yes [41] |
Keywords in URL, h1 or first words | Yes [16,17,18,19,28,29,30] | ? | ? | No [40] | No [41] | |
Keyword frequency | No [16,17,18,19] | ? | ? | Yes [40] | Yes [41] | |
Technical factors: design, speed, etc. | Yes [16,17,18,19,28,29,30] | ? | ? | No [40] | No [41] | |
Off-page factors | Backlinks | Yes [16,17,18,19,28,29,30] | ? | ? | No [40] | No [41] |
Received citations | ? | Yes [16,31,32,33,34] | Yes [35,36,37,38,64] | No [40] | No [41] | |
Author reputation | Yes [16,17,18,19,28,29,30] | Yes [16] | Yes [35,36,37,38,64] | No [40] | No [41] | |
Reputation of the publication or domain | Yes [16,17,18,19,28,29,30] | Yes [16] | Yes [35,36,37,38,64] | No [40] | No [41] | |
Signals from social networks | Yes (Indirect) [16,17,18,19] | ? | ? | No [40] | No [41] | |
Traffic, Click Through Rate | Yes [16,17,18,19,28,29,30] | ? | ? | No [40] | No [41] | |
Artificial intelligence | RankBrain | Yes [17,18,19,28,29,30] | ? | ? | No [40] | No [41] |
System | Number of Search Terms | Search Restrictions Included | Spearman’s Coefficient | p |
---|---|---|---|---|
Google Scholar | 1 | unrestricted | 0.968 | <0.0001 |
Google Scholar | 2 | unrestricted | 0.721 | <0.0001 |
Google Scholar | 1 | title | 0.990 | <0.0001 |
Google Scholar | 2 | title | 0.994 | <0.0001 |
Microsoft Academic | 1 | title, abstract, keywords | 0.907 | <0.0001 |
Microsoft Academic | 2 | title, abstract, keywords | 0.937 | <0.0001 |
Scopus | 2 | title, abstract, keywords | −0.107 | <0.001 |
WoS-version 1 | 2 | title, abstract, keywords | −0.075 | <0.05 |
Wos-version 2 | 2 | title, abstract, keywords | 0.907 | <0.0001 |
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Share and Cite
Rovira, C.; Codina, L.; Guerrero-Solé, F.; Lopezosa, C. Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus. Future Internet 2019, 11, 202. https://doi.org/10.3390/fi11090202
Rovira C, Codina L, Guerrero-Solé F, Lopezosa C. Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus. Future Internet. 2019; 11(9):202. https://doi.org/10.3390/fi11090202
Chicago/Turabian StyleRovira, Cristòfol, Lluís Codina, Frederic Guerrero-Solé, and Carlos Lopezosa. 2019. "Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus" Future Internet 11, no. 9: 202. https://doi.org/10.3390/fi11090202
APA StyleRovira, C., Codina, L., Guerrero-Solé, F., & Lopezosa, C. (2019). Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus. Future Internet, 11(9), 202. https://doi.org/10.3390/fi11090202