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
翻译：最近的研究表明社交媒体影响论文的科学影响。然而,这些研究只利用推特数字来代表Twitter活动。在本论文中,我们提出TweetPap,这是一个大规模数据集,介绍时间性引文/tweets信息以及推文元数据,以量化和理解社会媒体上科学论文的论述。该数据集可在https://github.com/lingo-iitgn/TweetPap上公开查阅。
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