Visualize ICLR 2022 OpenReview Data

ICLR 2022 Paper submission analysis from https://openreview.net/group?id=ICLR.cc/2022/Conference

Requirements

• Install requirements

pip install wordcloud nltk pandas imageio selenium tqdm

• Download nltk packages for language processing

import nltk
nltk.download('punkt')
nltk.download('averaged_perceptron_tagger')
nltk.download('wordnet')
nltk.download('stopwords')

• If you got anything wrong when calling webdriver.Edge('msedgedriver.exe'), you can

  • Delete msedgedriver.exe since it may only work on my computer (Windows 10)

  • Install Microsoft Edge (Chromium): Ensure you have installed Microsoft Edge (Chromium). To confirm that you have Microsoft Edge (Chromium) installed, go to edge://settings/help in the browser, and verify the version number is Version 75 or later.

  • Download Microsoft Edge Driver: Go to edge://settings/help to get the version of Edge.

  • Navigate to the Microsoft Edge Driver downloads page and download the driver that matches the Edge version number.

  From https://stackoverflow.com/questions/63529124/how-to-open-up-microsoft-edge-using-selenium-and-python

Crawl Data

1. Run crawl_paperlist.py to crawl the list of papers (~0.5h).

Paper List (3,407 submission in total)

crawl_paperlist.py only crawls 3,000 papers for some errors, but it has 3,407 submissions in total. The full paper list are as follows:

• sources/ICLR-2022.csv
• sources/ICLR-2022.md

Visualization

Keywords and Title

• 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.

• Title Keywords Frequency The top 50 common title keywords (uncased) and their frequency:

• Title Keywords Cloud The word clouds formed by keywords of submission titles:

Acknowledgment

Inspired by this repo: https://github.com/evanzd/ICLR2021-OpenReviewData