A Multilingual Similarity Dataset for News Article Frame

TL;DR

This paper introduces the largest multilingual news article similarity dataset with detailed annotations, enabling better analysis of news frames, media bias, and global news coverage across languages and countries.

Contribution

It presents an extensive, cross-lingual news article similarity dataset with pairwise comparisons and detailed annotations, facilitating research in media analysis and social sciences.

Findings

Largest multilingual news similarity dataset to date

Demonstrates potential in analyzing media bias and community detection

Enables new insights into global news coverage and perspectives

Abstract

Understanding the writing frame of news articles is vital for addressing social issues, and thus has attracted notable attention in the fields of communication studies. Yet, assessing such news article frames remains a challenge due to the absence of a concrete and unified standard dataset that considers the comprehensive nuances within news content. To address this gap, we introduce an extended version of a large labeled news article dataset with 16,687 new labeled pairs. Leveraging the pairwise comparison of news articles, our method frees the work of manual identification of frame classes in traditional news frame analysis studies. Overall we introduce the most extensive cross-lingual news article similarity dataset available to date with 26,555 labeled news article pairs across 10 languages. Each data point has been meticulously annotated according to a codebook detailing eight critical aspects of news content, under a human-in-the-loop framework. Application examples demonstrate its potential in unearthing country communities within global news coverage, exposing media bias among news outlets, and quantifying the factors related to news creation. We envision that this news similarity dataset will broaden our understanding of the media ecosystem in terms of news coverage of events and perspectives across countries, locations, languages, and other social constructs. By doing so, it can catalyze advancements in social science research and applied methodologies, thereby exerting a profound impact on our society.