This script extracts the historic word occurrence of a search term in academic papers (from Google Scholar). It allows for spotting trends in research and analyzing the relevance of a topic over time.
python extract_occurrences.py '<keyword>' <start date> <end date>
This command lists the number of publications for every year using this keyword. The script just searches for articles and excludes patents and citations.
The script requires a couple of packages (e.g. Beautiful Soup 4), you can install them with pip.
- Search term: 'bitcoin'
- Desired time span: 2000 to 2015
- (Optional) Output file: 'results/out.csv'
- Command:
python extract_occurrences.py 'bitcoin' 2000 2015 'results/out.csv' - Output:
results/out.csv(orout.csvby default), with the following contents:
| year | results |
|---|---|
| ... | ... |
| 2011 | 141 |
| 2012 | 292 |
| 2013 | 889 |
| 2014 | 2370 |
| 2015 | 2580 |
OSX only: Python 3.6 does not include any SSL certificates, therefore any https
request will fail due to the impossibility to verify the URL.
This will lead to the following error:
urllib.error.URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed
Fix: Execute /Applications/Python\ 3.6/Install\ Certificates.command to
install the certifi package. (More details: https://stackoverflow.com/a/42334357)
Created by Volker Strobel - [email protected]
If you use this code in academic papers, please cite this repository via Zenodo (http://doi.org/10.5281/zenodo.1218409):
Volker Strobel. (2018, April 14). Pold87/academic-keyword-occurrence: First release (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.1218409