Modeling and Analyzing the Video Game Live-Streaming Community

2014 9th Latin American Web Congress Pub Date : 2014-10-22 DOI:10.1109/LAWeb.2014.9

Gustavo Nascimento, Manoel Horta Ribeiro, L. Cerf, Natalia Cesario, Mehdi Kaytoue-Uberall, Chedy Raïssi, Thiago Vasconcelos, Wagner Meira Jr

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引用次数: 53

Abstract

In parallel to the exponential growth of the gaming industry, video game live-streaming is rising as a major form of online entertainment. Gathering a heterogeneous community, the popularity of this new media led to the creation of web services just for streaming video games, such as Twitch. TV. In this paper, we propose a model to characterize how streamers and spectators behave, based on their possible actions in Twitch and, using it, we perform a case study on the Star craft II streamers and spectators. In the case study we analyze a large amount of data collected in Twitch. TV's chat in order to better understand how streamers behave, and how this new form of online entertainment is different from previous ones. Based on this analysis, we were able to better understand channel switching, channel surfing, and to create a model for predicting the number of chat messages based on the number of spectators. We were also able to describe behavioral patterns, such as the mass evasion of spectators before the end of a streaming section in a channel.

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建模和分析电子游戏直播社区

随着游戏产业的指数级增长，视频游戏直播作为一种主要的在线娱乐形式正在崛起。聚集了一个异质的社区，这种新媒体的流行导致了专门用于流媒体视频游戏的网络服务的创建，比如Twitch。电视。在本文中，我们提出了一个模型来描述主播和观众的行为，基于他们在Twitch中的可能行为，并使用它，我们对《星际争霸2》的主播和观众进行了案例研究。在案例研究中，我们分析了从Twitch收集的大量数据。为了更好地了解流媒体的行为，以及这种新的在线娱乐形式与以前的娱乐形式有何不同。基于此分析，我们能够更好地理解频道切换、频道浏览，并创建一个模型，用于根据观众数量预测聊天消息的数量。我们还能够描述行为模式，例如在一个频道的流媒体部分结束之前，观众大量逃避。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2014 9th Latin American Web Congress

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