Don't just watch, join in: Exploring information behavior and copresence on Twitch
Don't just watch, join in: Exploring information behavior and copresence on Twitch
复制标题
DOI：
10.1016/j.chb.2019.106221
复制
发表时间：
2020-04-01
影响因子：
9.9
通讯作者：
Sellers, Nicholas
中科院分区：
文献类型：
--
作者：
Diwanji, Vaibhav;Reed, Abigail;Sellers, Nicholas
这项混合方法的研究探讨了用户的信息行为和他们的感知的同现在Twitch。电视，数百万人每天聚集在一起直播，互动，并制作自己的娱乐节目。人类信息理论模型和社会认同理论构成了本研究的理论框架。研究特定主题的流媒体直播服务是通信领域一个新兴而令人兴奋的领域。特定主题的实时流媒体网站，如Twitch.tv，正在不断发展成为重要的信息来源，补充了传统的信息系统，如图书馆和在线搜索引擎网站，如谷歌。使用语言查询和字数统计（LIWC）和SPSS统计工具分析了Twitch.tv上三个实时流的聊天记录。使用Nvivo 12进行定性专题分析。信息反应和信息生产是三种信息流中最常见的信息行为。定性分析表明，用户在三个直播流表现出很大的共现。这项研究是重要的第一步，为理解Twitch，特定主题直播网站和一般社交直播网站上的人类信息行为提供理论见解。
This mixed-methods study examined users' information behavior and their perceptions of copresence on Twitch. tv, where millions of people come together live every day to stream, interact, and make their own entertainment. Human information theory model and social identity theory constituted the theoretical framework for this research. Studying topic specific live streaming services is an emerging and exciting field in communication. Topic specific live streaming sites such as Twitch.tv are evolving constantly into important sources of information that complement the traditional information systems such as libraries and online search engine sites like Google. Chat logs of three live streams on Twitch.tv were analyzed using Linguistic Query and Word Count (LIWC) and SPSS statistical tools. Qualitative thematic analysis was carried out using Nvivo 12. Information reaction and production were the most frequent information behaviors across three streams. Qualitative analysis indicated that users within the three live streams showed a great deal of copresence. This study is an important first step to provide theoretical insights into understanding human information behavior on Twitch, topic specific live streaming sites, and social live streaming sites in general.