CS-lol: a Dataset of Viewer Comment with Scene in E-sports Live-streaming

• URL: http://arxiv.org/abs/2301.06876v1
• Date: Tue, 17 Jan 2023 13:34:06 GMT
• Title: CS-lol: a Dataset of Viewer Comment with Scene in E-sports Live-streaming
• Authors: Junjie H. Xu and Yu Nakano and Lingrong Kong and Kojiro Iizuka
• Abstract summary: Billions of live-streaming viewers share their opinions on scenes they are watching in real-time and interact with the event. We develop CS-lol, a dataset containing comments from viewers paired with descriptions of game scenes in E-sports live-streaming. We propose a task, namely viewer comment retrieval, to retrieve the viewer comments for the scene of the live-streaming event.
• Score: 0.5735035463793008
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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