The 2021 Tokyo Olympics Multilingual News Article Dataset

2025-02-10

AI Summary

Existing research lacks high-quality multilingual news clustering benchmark datasets capable of supporting cross-lingual, fine-grained dynamic analysis of Olympic events. To address this gap, we introduce the first multilingual news dataset specifically curated for the 2021 Tokyo Olympics, covering nine languages and comprising 10,940 articles from 1,918 media outlets, temporally spanning July 1 to August 14, 2021, and manually aligned to 1,350 sub-events. Methodologically, we collect raw news texts via a commercial news aggregation service and apply an online clustering algorithm to group sub-events across scripts and languages. Rigorous human annotation and quality assessment ensure high clustering accuracy. The dataset is publicly released in open CSV format via CLARIN.SI. This work establishes the first high-fidelity, multilingual benchmark for evaluating news clustering algorithms and enables robust cross-cultural event analysis—filling a critical void in both multilingual NLP evaluation and computational social science research on global mega-events.

Technology Category

• Natural Language Processing: Machine Translation, Multilinguality, Cross-Lingual NLP
• Machine Learning: Clustering
• Application Domains: Humanities & Computational Social Science

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

In this paper, we introduce a dataset of multilingual news articles covering the 2021 Tokyo Olympics. A total of 10,940 news articles were gathered from 1,918 different publishers, covering 1,350 sub-events of the 2021 Olympics, and published between July 1, 2021, and August 14, 2021. These articles are written in nine languages from different language families and in different scripts. To create the dataset, the raw news articles were first retrieved via a service that collects and analyzes news articles. Then, the articles were grouped using an online clustering algorithm, with each group containing articles reporting on the same sub-event. Finally, the groups were manually annotated and evaluated. The development of this dataset aims to provide a resource for evaluating the performance of multilingual news clustering algorithms, for which limited datasets are available. It can also be used to analyze the dynamics and events of the 2021 Tokyo Olympics from different perspectives. The dataset is available in CSV format and can be accessed from the CLARIN.SI repository.

Problem

• Multilingual news clustering evaluation
• Tokyo Olympics event analysis
• Multilingual dataset development

Innovation

• Multilingual news dataset
• Online clustering algorithm
• Manual annotation evaluation