Invasion@Ukraine: Providing and Describing a Twitter Streaming Dataset That Captures the Outbreak of War between Russia and Ukraine in 2022

J. Pohl, Simon Markmann, Dennis Assenmacher, C. Grimme
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引用次数: 1

Abstract

Social media can be a mirror of human interaction, society, and historic disruptions. Their reach enables the global dissemination of information in the shortest possible time and, thus, the individual participation of people worldwide in global events in almost real-time. However, these platforms can be equally efficiently used in information warfare to manipulate human perception and opinion formation. Within this paper, we describe a dataset of raw tweets collected via the Twitter Streaming API in the context of the onset of the war, which Russia started in Ukraine on February 24, 2022. A distinctive feature of the dataset is that it covers the period from one week before to one week after Russia invasion of Ukraine. This paper details the acquisition process and provides first insights into the content of the data stream. In addition, the data has been annotated with availability tags, resulting from rehydration attempts at two points in time: directly after data acquisition and shortly before manuscript submission. This may provide information on Twitter moderation policies. Further, we provide a detailed list of other published dataset covering the same topic. On the content level, we can show that our dataset comprises several distinct topics related to the conflict and conspiracy narratives -- topics that deserve more profound investigation. Therefore, the presented dataset is also made available to the community in an extended version with pseudonymized tweet content upon request.
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Invasion@Ukraine:提供并描述一个Twitter流数据集,该数据集捕捉了2022年俄罗斯和乌克兰之间爆发的战争
社交媒体可以是人类互动、社会和历史中断的一面镜子。它们的覆盖范围使信息能够在尽可能短的时间内在全球传播,从而使世界各地的人们几乎实时地单独参与全球事件。然而,这些平台同样可以有效地用于信息战,以操纵人类的感知和意见形成。在本文中,我们描述了一个通过Twitter Streaming API在战争开始的背景下收集的原始推文数据集,俄罗斯于2022年2月24日在乌克兰发动了战争。该数据集的一个显著特征是,它涵盖了俄罗斯入侵乌克兰前一周到后一周的时间。本文详细介绍了获取过程,并提供了对数据流内容的初步见解。此外,数据已经标注了可用性标签,这是在两个时间点进行补液尝试的结果:数据获取后和投稿前不久。这可能提供有关Twitter审核政策的信息。此外,我们还提供了涵盖相同主题的其他已发布数据集的详细列表。在内容层面上,我们可以展示我们的数据集包含与冲突和阴谋叙事相关的几个不同主题——这些主题值得更深入的研究。因此,所呈现的数据集也可应要求以扩展版本提供给社区,其中包含假名tweet内容。
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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