mlsanityData to 14 Oct 2026

Unveiling Global Narratives: A Multilingual Twitter Dataset of News Media on the Russo-Ukrainian Conflict

arXiv 2306.12886 ↗First posted 22 Jun 2023cs.CL cs.DLcited by 1

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Abstract (arXiv)

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 multimedia 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 along with their images. Each entry in the dataset is accompanied by processed tags, allowing for the identification of entities, stances, textual or visual concepts, and sentiment. The availability of this multimedia 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 from, how are the different textual and visual concepts related to the event portrayed.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 15 of its 23 references that are in the map. First posted on arXiv 22 Jun 2023.

Builds on

15 of 23 references.

References · 15

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3 more
  1. 2022Twitter Dataset on the Russo-Ukrainian Warcited by 3
  2. 2022Characterizing the 2022 Russo-Ukrainian Conflict Through the Lenses of Aspect-Based Sentiment Analysis: Dataset, Methodology, and Preliminary Findingscited by 1
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