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SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search

Hope, T.; Portenoy, J.; Vasan, K.; Borchardt, J.; Horvitz, E.; Weld, D. S.; Hearst, M. A.; West, J.

2020-10-20 bioinformatics
10.1101/2020.05.23.112284 bioRxiv
Show abstract

The COVID-19 pandemic has sparked unprecedented mobilization of scientists, generating a deluge of papers that makes it hard for researchers to keep track and explore new directions. Search engines are designed for targeted queries, not for discovery of connections across a corpus. In this paper, we present SciSight, a system for exploratory search of COVID-19 research integrating two key capabilities: first, exploring associations between biomedical facets automatically extracted from papers (e.g., genes, drugs, diseases, patient outcomes); second, combining textual and network information to search and visualize groups of researchers and their ties. SciSight1 has so far served over 15K users with over 42K page views and 13% returns.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
Bioinformatics
◐ 1204 papers in training set
Top 3%
9.4%
Similar papers in this journal
2
GigaScience
◐ 212 papers in training set
Top 0.2%
8.7%
Similar papers in this journal
3
Bioinformatics Advances
◐ 203 papers in training set
Top 0.7%
6.6%
Similar papers in this journal
4
PLOS ONE
● 5266 papers in training set
Top 28%
5.3%
Similar papers in this journal
5
BMC Bioinformatics
○ 457 papers in training set
Top 2%
5.3%
Similar papers in this journal
6
Patterns
○ 78 papers in training set
Top 0.3%
4.7%
7
Journal of Medical Internet Research
◐ 87 papers in training set
Top 0.6%
4.3%
8
Journal of the American Medical Informatics Association
◐ 71 papers in training set
Top 0.9%
3.4%
9
IEEE Access
● 35 papers in training set
Top 0.3%
3.3%
50% of probability mass above
10
Journal of Biomedical Informatics
○ 47 papers in training set
Top 0.5%
3.1%
11
Nucleic Acids Research
◐ 1281 papers in training set
Top 6%
3.1%
12
PLOS Computational Biology
● 1863 papers in training set
Top 11%
2.7%
13
Genome Biology
○ 637 papers in training set
Top 5%
2.4%
14
Scientific Reports
○ 3612 papers in training set
Top 43%
2.3%
15
Database
◐ 61 papers in training set
Top 0.4%
1.9%
16
Briefings in Bioinformatics
◐ 354 papers in training set
Top 5%
1.7%
17
JAMIA Open
◐ 42 papers in training set
Top 1.0%
1.6%
18
PLOS Digital Health
● 106 papers in training set
Top 3%
1.5%
19
eLife
● 5828 papers in training set
Top 55%
1.4%
20
Computers in Biology and Medicine
○ 128 papers in training set
Top 3%
1.4%
21
Nature Communications
○ 5641 papers in training set
Top 49%
1.3%
22
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 4%
1.3%
23
Nature Methods
○ 385 papers in training set
Top 6%
1.1%
24
Cell Systems
○ 201 papers in training set
Top 4%
1.1%
25
BioData Mining
○ 22 papers in training set
Top 0.4%
1.1%
26
iScience
○ 1154 papers in training set
Top 31%
1.0%
27
Frontiers in Systems Biology
○ 10 papers in training set
Top 0.2%
0.8%
28
IEEE/ACM Transactions on Computational Biology and Bioinformatics
● 38 papers in training set
Top 1%
0.8%
29
Frontiers in Genetics
○ 230 papers in training set
Top 6%
0.8%
30
IEEE Transactions on Computational Biology and Bioinformatics
● 20 papers in training set
Top 0.7%
0.8%

"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.