TweetPap: A Dataset to Study the Social Media Discourse of Scientific Papers

Naman Jain, M. Singh
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引用次数: 1

Abstract

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.
TweetPap:一个研究科学论文的社交媒体话语的数据集
如今,研究人员已经转向像Twitter这样的平台来传播有关他们的想法和经验证据的信息。最近的研究表明,社交媒体会影响一篇论文的科学影响力。然而,这些研究仅利用tweet计数来表示Twitter活动。在本文中,我们提出了一个大规模数据集TweetPap,该数据集引入了引用/推文的时间信息和推文的元数据,以量化和理解社交媒体上科学论文的话语。该数据集可在https://github.com/lingo-iitgn/TweetPap上公开获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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