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Scholar Metrics Scraper (SMS): automated retrieval of citation and author data

Cheung, N. A.; Giustini, D.; LeDue, J.; Murphy, T. H.

2021-12-25 scientific communication and education
10.1101/2021.12.23.473883 bioRxiv
Show abstract

Academic departments, research clusters and evaluators analyze author and citation data to measure research impact and to support strategic planning. We created a tool, Scholar Metrics Scraper (SMS), to automate the retrieval of this bibliometric data for our research team. The project contains Jupyter notebooks (publicly-shared here) that take a list of researchers as an input to export a CSV file of citation metrics from Google Scholar and figures to visualize the groups impact. SMS is a scalable, open and publicly-accessible solution for automating the retrieval of citation data over time for a group of researchers.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Bioinformatics
◐ 1204 papers in training set
Top 1%
18.9%
Similar papers in this journal
2
eLife
● 5828 papers in training set
Top 6%
12.9%
Similar papers in this journal
3
Bioinformatics Advances
◐ 203 papers in training set
Top 0.2%
10.0%
Similar papers in this journal
4
PLOS ONE
● 5266 papers in training set
Top 23%
6.9%
Similar papers in this journal
5
Ecology and Evolution
○ 267 papers in training set
Top 1%
4.9%
Similar papers in this journal
50% of probability mass above
6
F1000Research
○ 88 papers in training set
Top 0.3%
4.1%
7
eneuro
● 439 papers in training set
Top 2%
3.5%
8
FACETS
● 14 papers in training set
Top 0.1%
3.3%
9
PeerJ
◐ 308 papers in training set
Top 2%
3.3%
10
Behavior Research Methods
○ 30 papers in training set
Top 0.3%
1.9%
11
Heliyon
○ 152 papers in training set
Top 3%
1.8%
12
PLOS Computational Biology
● 1863 papers in training set
Top 14%
1.8%
13
Frontiers in Artificial Intelligence
○ 20 papers in training set
Top 0.3%
1.5%
14
GigaScience
◐ 212 papers in training set
Top 3%
1.4%
15
Frontiers in Bioinformatics
○ 49 papers in training set
Top 0.8%
1.1%
16
Frontiers in Behavioral Neuroscience
○ 49 papers in training set
Top 0.7%
1.1%
17
Wellcome Open Research
○ 67 papers in training set
Top 0.7%
1.1%
18
Research Synthesis Methods
○ 20 papers in training set
Top 0.2%
1.1%
19
Ecological Informatics
○ 33 papers in training set
Top 0.6%
1.1%
20
Cell Systems
○ 201 papers in training set
Top 4%
1.1%
21
iMeta
○ 10 papers in training set
Top 0.1%
1.1%
22
PLOS Digital Health
● 106 papers in training set
Top 4%
0.9%
23
FEBS Open Bio
○ 31 papers in training set
Top 0.8%
0.9%
24
BMC Research Notes
○ 33 papers in training set
Top 1%
0.9%
25
Sustainability
○ 10 papers in training set
Top 0.4%
0.9%
26
Gigabyte
● 62 papers in training set
Top 1%
0.9%
27
PLANTS, PEOPLE, PLANET
○ 27 papers in training set
Top 0.7%
0.6%
28
FASEB BioAdvances
○ 18 papers in training set
Top 0.5%
0.6%
29
BMC Medical Research Methodology
○ 47 papers in training set
Top 1%
0.6%
30
Acta Crystallographica Section D Structural Biology
● 59 papers in training set
Top 0.5%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.