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Dank or Not

Supplementary data for the paper the Dank or Not? -- Analyzing and Predicting Popularity of Memes on Reddit - Barnes et al. (2020)

How to Cite

  title={Dank or not? Analyzing and predicting the popularity of memes on Reddit},
  author={Barnes, Kate and Riesenmy, Tiernon and Trinh, Minh Duc and Lleshi, Eli and Balogh, N{\'o}ra and Molontay, Roland},
  journal={Applied Network Science},


The data is scraped using a Pushshift API, and it consists of all posts starting from March 17th, 2020 to March 23rd, 2020 across these Reddit subreddits:

Summary of Data

After cleaning, we end up with 80,362 posts that are used as training/testing data for our machine learning models. This spreadsheet contains the posts with their metadata as well as the generated attributes we used in the paper.

Feature Type Description
created_utc UTC timestamp time of post submission
ups integer number of upvotes received
is_nsfw boolean indicates if only suitable for 18+
subreddit string subreddit of the submission
subscribers integer number of subscribers to the subreddit
thumbnail.height floating point value height of the thumbnail
thumbnail.thumbnail string thumbnail media
thumbnail.width floating point value width of thumbnail
title string title of the submission
media string link to associated meme media
ups_normed floating point value ups normalized with subscribers
dank_level integer label ups_normed for binary classification
processed_words list of strings filtered and stemmed words from title and image
word_count integer number of words in title and image
TextLength integer number of characters in title
Sentiment floating point value text valence score
avg_hue floating point value average HSV hue value of meme
avg_saturation floating point value average HSV saturation value of meme
avg_value floating point value average HSV value value of meme
30 colors floating point value normalized pixels of color in image
VGG_features list of strings VGG-16's first three guesses about image content
VGG_probs list of floating point values the probabilities of the VGG-16's first three guesses

Raw Image Files

For the Convoluted Neural Network section of the paper, we download and sample from the 76,000+ downloadable images provided in the media field of the posts. The raw image files can be found in the data folder.

dank not_dank Total
Training set 1,856 1,856 3,712
Validation set 928 928 1,856
Test set 929 929 1,858
Total 3,713 3,713 7,426

Random Forest

The notebook for the Random Forest model along with some supplementary analysis for the model can be found in the notebook folder.

A more detailed description of the dataset and how we generate our attributes can be found in Dank or Not? -- Analyzing and Predicting Popularity of Memes on Reddit

Image Analysis

The notebooks for the image analysis and features extraction can be found in the notebook folder.

Final plots and a more detailed description can be found in the Image Analysis section of Dank or Not? -- Analyzing and Predicting Popularity of Memes on Reddit


Supplementary data for the paper *Dank or Not? -- Analyzing and Predicting the Popularity of Memes on Reddit*






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