Unveiling Global Narratives: A Multilingual Twitter Dataset of News Media on the Russo-Ukrainian Conflict
Hakimov, Sherzod, Cheema, Gullal S.
–arXiv.org Artificial Intelligence
The ongoing Russo-Ukrainian conflict has been a subject of intense media coverage worldwide. Understanding the global narrative surrounding this topic is crucial for researchers that aim to gain insights into its multifaceted dimensions. In this paper, we present a novel dataset that focuses on this topic by collecting and processing tweets posted by news or media companies on social media across the globe. We collected tweets from February 2022 to May 2023 to acquire approximately 1.5 million tweets in 60 different languages. Each tweet in the dataset is accompanied by processed tags, allowing for the identification of entities, stances, concepts, and sentiments expressed. The availability of the dataset serves as a valuable resource for researchers aiming to investigate the global narrative surrounding the ongoing conflict from various aspects such as who are the prominent entities involved, what stances are taken, where do these stances originate, and how are the different concepts related to the event portrayed.
arXiv.org Artificial Intelligence
Jun-22-2023
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