  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
