This Jupyter Notebook contains the data crawled from ICLR 2021 OpenReview webpages and their visualizations. The list of submissions (sorted by the average ratings) can be found here.
- python 3.7
- selenium
- pandas
- seaborn
- imageio
- wordcloud
- tqdm
edgewebdriver
- NOTE: You can also use
chromedriver
by settingdriver = webdriver.Chrome('chromedriver.exe')
.
- NOTE: You can also use
- Run
crawl_paperlist.py
to crawl the list of papers (~0.5h). - Run
crawl_reviews.py
to crawl the reviews (~1.5h).- NOTE: currently only review ratings are crawled.
Keywords Frequency
The top 50 common keywords (uncased) and their frequency:
Keywords Cloud
The word clouds formed by keywords of submissions show the hot topics including deep learning, reinforcement learning, representation learning, graph neural network, etc.
Ratings Distribution
The distribution of reviewer ratings centers around 5 (mean: 5.367).
Keywords vs Ratings
The average reviewer ratings and the frequency of keywords indicate that to maximize your chance to get higher ratings would be using the keywords such as deep generative models, or normalizing flows.
All ICLR 2021 Submissions
Number of submissions: 2966 (Collected at 11/11/2020 09:11 AM UTC+8).
Visualizations are inspired by this repo: https://github.com/shaohua0116/ICLR2020-OpenReviewData.