Kai Nakamura, Sharon Levy, and William Yang Wang. 2019. r/Fakeddit: A New Multimodal Benchmark Dataset for Fine-grained Fake News Detection It's not a subreddit. It's named Fakeddit because Fake News + Reddit = Fakeddit
Paper: https://arxiv.org/abs/1911.03854
Our lab: http://nlp.cs.ucsb.edu/index.html
Follow the instructions to download the dataset. You can download text, metadata, comment data, and image data.
Note that released test set is public. Private test set is used for leaderboard.
Please let us know if you encounter any problems by opening an issue or by directly contacting us.
Download the v1.0 dataset from here
Download the comment data from here
The *.tsv dataset files have an image_url column which contain the image urls.
For convenience, we have provided a script which will download the images for you. Please follow the instructions if you would like to use the attached script.
Fork or clone this repository and install required python libraries
$ git clone https://github.com/entitize/Fakeddit
$ cd Fakeddit
$ pip install -r requirements.txt
Copy image_downloader.py to the same directory/folder as where you downloaded the tsv files.
Run image_downloader.py in the new directory/folder
$ python image_downloader.py file
substitute file with either train.tsv, validate.tsv, or test.tsv
Note that you must run the image_downloader.py script 3 times to download the entire public dataset
train.tsv, validate.tsv, and test.tsv contain text and metadata for the training, validation, and public testing datasets respectively.
comments.tsv consists of comments made by Reddit users on submissions in the entire released dataset. Use the submission_id column to identify which submission the comment is associated with. Note that one submission can have zero, one, or multiple comments.