CS-lol: a Dataset of Viewer Comment with Scene in E-sports Live-streaming
Billions of live-streaming viewers share their opinions on scenes they are watching in real-time and interact with the event, commentators as well as other viewers via text comments. Thus, there is necessary to explore viewers' comments with scenes in E-sport live-streaming events. In this paper, we developed CS-lol, a new large-scale dataset containing comments from viewers paired with descriptions of game scenes in E-sports live-streaming. Moreover, we propose a task, namely viewer comment retrieval, to retrieve the viewer comments for the scene of the live-streaming event. Results on a series of baseline retrieval methods derived from typical IR evaluation methods show our task as a challenging task. Finally, we release CS-lol and baseline implementation to the research community as a resource.
Code (1)
Tasks
RetrievalSimilar Papers 제목 키워드 기반
Game-MUG: Multimodal Oriented Game Situation Understanding and Commentary Generation Dataset
The dynamic nature of esports makes the situation relatively complicated for average viewers. Esports broadcasting involves game expert casters, but the caster-dependent game commentary is not enough to fully understand …
Time SeriesGenerating Sports News from Live Commentary: A Chinese Dataset for Sports Game Summarization
Sports game summarization focuses on generating news articles from live commentaries. Unlike traditional summarization tasks, the source documents and the target summaries for sports game summarization tasks are written …
ArticlesKnowledge Enhanced Sports Game Summarization
Sports game summarization aims at generating sports news from live commentaries. However, existing datasets are all constructed through automated collection and cleaning processes, resulting in a lot of noise. Besides, c…
Buzz to Broadcast: Predicting Sports Viewership Using Social Media Engagement
Accurately predicting sports viewership is crucial for optimizing ad sales and revenue forecasting. Social media platforms, such as Reddit, provide a wealth of user-generated content that reflects audience engagement and…
Sentiment AnalysisLiveChat: Video Comment Generation from Audio-Visual Multimodal Contexts
Live commenting on video, a popular feature of live streaming platforms, enables viewers to engage with the content and share their comments, reactions, opinions, or questions with the streamer or other viewers while wat…
Comment GenerationDiversitymultimodal generation