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

TL;DR

This paper introduces a comprehensive multilingual Twitter dataset of news media posts about the Russo-Ukrainian conflict, enabling analysis of global narratives through textual and visual data.

Contribution

It provides a novel, large-scale multimedia dataset with processed tags for entity, stance, concept, and sentiment analysis related to the conflict.

Findings

Approximately 1.5 million tweets collected in 60 languages

Includes images and processed tags for detailed analysis

Facilitates research on global media narratives

Abstract

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.