#Election2020: the first public Twitter dataset on the 2020 US Presidential election.

IF 2 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Journal of Computational Social Science Pub Date : 2022-01-01 Epub Date: 2021-04-02 DOI:10.1007/s42001-021-00117-9
Emily Chen, Ashok Deb, Emilio Ferrara
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引用次数: 50

Abstract

Credible evidence-based political discourse is a critical pillar of democracy and is at the core of guaranteeing free and fair elections. The study of online chatter is paramount, especially in the wake of important voting events like the recent November 3, 2020 U.S. Presidential election and the inauguration on January 21, 2021. Limited access to social media data is often the primary obstacle that limits our abilities to study and understand online political discourse. To mitigate this impediment and empower the Computational Social Science research community, we are publicly releasing a massive-scale, longitudinal dataset of U.S. politics- and election-related tweets. This multilingual dataset encompasses over 1.2 billion tweets and tracks all salient U.S. political trends, actors, and events from 2019 to the time of this writing. It predates and spans the entire period of the Republican and Democratic primaries, with real-time tracking of all presidential contenders on both sides of the aisle. The dataset also focuses on presidential and vice-presidential candidates, the presidential elections and the transition from the Trump administration to the Biden administration. Our dataset release is curated, documented, and will continue to track relevant events. We hope that the academic community, computational journalists, and research practitioners alike will all take advantage of our dataset to study relevant scientific and social issues, including problems like misinformation, information manipulation, conspiracies, and the distortion of online political discourse that has been prevalent in the context of recent election events in the United States. Our dataset is available at: https://github.com/echen102/us-pres-elections-2020.

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#Election2020:关于2020年美国总统大选的第一个公开推特数据集。
可信的、基于证据的政治话语是民主的重要支柱,也是保证自由公正选举的核心。对网络聊天的研究至关重要,尤其是在重要的投票事件之后,比如最近的2020年11月3日美国总统大选和2021年1月21日的就职典礼。对社交媒体数据的有限访问往往是限制我们学习和理解在线政治话语能力的主要障碍。为了减轻这一障碍并增强计算社会科学研究界的能力,我们公开发布了一个大规模的美国政治和选举相关推文纵向数据集。这个多语言数据集包含超过12亿条推文,并跟踪了从2019年到撰写本文时所有重要的美国政治趋势、演员和事件。它早于共和党和民主党初选的整个时期,并对两党所有总统候选人进行实时跟踪。该数据集还关注总统和副总统候选人、总统选举以及从特朗普政府到拜登政府的过渡。我们的数据集发布是经过策划、记录的,并将继续跟踪相关事件。我们希望学术界、计算记者和研究从业者都能利用我们的数据集来研究相关的科学和社会问题,包括错误信息、信息操纵、阴谋和在美国最近的选举事件中普遍存在的在线政治话语扭曲等问题。我们的数据集可在:https://github.com/echen102/us-pres-elections-2020。
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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来源期刊
Journal of Computational Social Science
Journal of Computational Social Science SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
6.20
自引率
6.20%
发文量
30
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