@article{Xue2026, 
author = {Wenting Xue and Tianchen Luo and Qinglan Wei and Yuan Zhang},
title = {CCSS: A Multimodal Dataset for Cross-Cultural Sentiment Analysis and Sporting Spirit Communication in Competitive Sports},
year = {2026},
journal = {Journal of Social Computing},
volume = {7},
number = {3},
pages = {255-268},
keywords = {multimodal dataset, cross-cultural sentiment analysis, competitive sports, sporting spirit communication},
url = {https://www.sciopen.com/article/10.23919/JSC.2026.0009},
doi = {10.23919/JSC.2026.0009},
abstract = {The Cross-Cultural Sports Sentiment (CCSS) dataset is a multimodal resource for sentiment analysis and cultural communication in competitive sports. It integrates multi-source, multilingual data from global social media platforms such as Sina Weibo, Reddit, Twitter, Facebook, and YouTube, together with reports from 117 domestic and international news outlets, resulting in a multimodal corpus comprising over 9955 comment interactions, 886 news articles, and 876 min of video. Built around 60 key competitive events involving twelve elite athletes from China and abroad, and collected within time windows centered on athletes’ key competitive events, the dataset captures the temporal evolution of public opinion and emotion after events; by incorporating geo-cultural factors of competitions, it reveals the cross-cultural diffusion mechanisms of sporting spirit. The dataset provides a benchmark platform for cross-modal semantic understanding and offers a standardized evaluation framework for research on multimodal artificial intelligence (AI) in cross-cultural sentiment computation and modeling of sporting spirit communication.}
}