Nowadays, researchers have moved to platforms like Twitter to spread information about their ideas and empirical evidence. Recent studies have shown that social media affects the scientific impact of a paper. However, these studies only utilize the tweet counts to represent Twitter activity. In this paper, we propose TweetPap, a large-scale dataset that introduces temporal information of citation/tweets and the metadata of the tweets to quantify and understand the discourse of scientific papers on social media. The dataset is publicly available at https://github.com/lingo-iitgn/TweetPap
@article{arxiv.2106.07213,
title = {TweetPap: A Dataset to Study the Social Media Discourse of Scientific Papers},
author = {Naman Jain and Mayank Singh},
journal= {arXiv preprint arXiv:2106.07213},
year = {2021}
}