Uncovering the potential of Twitch as a source for social media metrics

Q2 Computer Science

First Monday Pub Date : 2024-01-03 DOI:10.5210/fm.v29i1.13214

Enrique Orduña-Malea, Carlos Lopezosa

{"title":"Uncovering the potential of Twitch as a source for social media metrics","authors":"Enrique Orduña-Malea, Carlos Lopezosa","doi":"10.5210/fm.v29i1.13214","DOIUrl":null,"url":null,"abstract":"The social live streaming service Twitch was launched in 2008 as Justin.tv, rebranded as Twitch Interactive in 2011, and acquired by Amazon in 2014. Although launched originally as a portal to broadcast videogames, Twitch currently hosts a wide range of content, including science and technology channels. Yet, despite growing interest in this online video sharing platform, Twitch’s potential for the study of science videos has been underexploited to date. This paper seeks to go some way to remedying this by studying the potential of Twitch as a data source for social media academic metrics. To do so, a scientometrics-inspired framework (the OBA framework) is proposed to integrate the analysis of Twitch, science videos and research organizations under a common conceptual space. Then, a science-related Twitch channel — National Aeronautics and Space Administration (NASA) — is used as a case study. We analyse 197 videos published by NASA between March 2017 and December 2022, as well as 51,935 clips created from NASA videos. Data were collected from the official Twitch API, which is also analysed to identify the units and metrics available and the channel’s performance in retrospective quantitative studies (i.e., non-live broadcasts). The results show that Twitch allows in-depth metric analyses of science videos to be undertaken, facilitating identification of both the activity and output-level impact of a scientific organization such as NASA. However, the Twitch API presents a few constraints, due, in the main, to the limited availability of many metrics that are restricted in time range, quantity, accuracy, or access, and which as such limit comprehensive retrospective studies. Despite these technical limitations, it is estimated that Twitch offers considerable potential for the study of science-related activity. The OBA model proposed facilitates the analysis of the activity of specific scientific agents (not only organizations but journals or other aggregates) under a conceptual framework based on approaches applied in quantitative studies of science.","PeriodicalId":38833,"journal":{"name":"First Monday","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"First Monday","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5210/fm.v29i1.13214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}

引用次数: 0

Abstract

The social live streaming service Twitch was launched in 2008 as Justin.tv, rebranded as Twitch Interactive in 2011, and acquired by Amazon in 2014. Although launched originally as a portal to broadcast videogames, Twitch currently hosts a wide range of content, including science and technology channels. Yet, despite growing interest in this online video sharing platform, Twitch’s potential for the study of science videos has been underexploited to date. This paper seeks to go some way to remedying this by studying the potential of Twitch as a data source for social media academic metrics. To do so, a scientometrics-inspired framework (the OBA framework) is proposed to integrate the analysis of Twitch, science videos and research organizations under a common conceptual space. Then, a science-related Twitch channel — National Aeronautics and Space Administration (NASA) — is used as a case study. We analyse 197 videos published by NASA between March 2017 and December 2022, as well as 51,935 clips created from NASA videos. Data were collected from the official Twitch API, which is also analysed to identify the units and metrics available and the channel’s performance in retrospective quantitative studies (i.e., non-live broadcasts). The results show that Twitch allows in-depth metric analyses of science videos to be undertaken, facilitating identification of both the activity and output-level impact of a scientific organization such as NASA. However, the Twitch API presents a few constraints, due, in the main, to the limited availability of many metrics that are restricted in time range, quantity, accuracy, or access, and which as such limit comprehensive retrospective studies. Despite these technical limitations, it is estimated that Twitch offers considerable potential for the study of science-related activity. The OBA model proposed facilitates the analysis of the activity of specific scientific agents (not only organizations but journals or other aggregates) under a conceptual framework based on approaches applied in quantitative studies of science.

查看原文本刊更多论文

挖掘 Twitch 作为社交媒体指标来源的潜力

社交流媒体直播服务 Twitch 于 2008 年作为 Justin.tv 推出，2011 年更名为 Twitch Interactive，2014 年被亚马逊收购。虽然 Twitch 最初是作为一个视频游戏直播门户网站推出的，但目前已拥有广泛的内容，包括科学和技术频道。然而，尽管人们对这一在线视频共享平台的兴趣与日俱增，但迄今为止，Twitch 在科学视频研究方面的潜力尚未得到充分挖掘。本文试图通过研究 Twitch 作为社交媒体学术指标数据源的潜力来弥补这一不足。为此，本文提出了一个受科学计量学启发的框架（OBA 框架），将 Twitch、科学视频和研究组织的分析整合到一个共同的概念空间中。然后，以一个与科学相关的 Twitch 频道--美国国家航空航天局（NASA）--为案例进行研究。我们分析了美国国家航空航天局在 2017 年 3 月至 2022 年 12 月期间发布的 197 个视频，以及根据美国国家航空航天局视频制作的 51935 个剪辑。我们从 Twitch 官方 API 收集数据，并对其进行分析，以确定可用的单位和指标，以及该频道在回顾性定量研究（即非直播）中的表现。结果表明，Twitch 可以对科学视频进行深入的度量分析，从而有助于确定像美国国家航空航天局（NASA）这样的科学组织在活动和产出层面的影响。不过，Twitch API 也存在一些限制，主要是由于许多指标的可用性有限，在时间范围、数量、准确性或访问方面受到限制，因此限制了全面的回顾性研究。尽管存在这些技术限制，但据估计，Twitch 为科学相关活动的研究提供了相当大的潜力。所提出的 OBA 模型有助于在一个基于科学定量研究方法的概念框架下，分析特定科学主体（不仅是组织，还有期刊或其他集合体）的活动。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

First Monday Computer Science-Computer Networks and Communications

CiteScore

2.20

自引率

0.00%

发文量

期刊介绍： First Monday is one of the first openly accessible, peer–reviewed journals on the Internet, solely devoted to the Internet. Since its start in May 1996, First Monday has published 1,035 papers in 164 issues; these papers were written by 1,316 different authors. In addition, eight special issues have appeared. The most recent special issue was entitled A Web site with a view — The Third World on First Monday and it was edited by Eduardo Villanueva Mansilla. First Monday is indexed in Communication Abstracts, Computer & Communications Security Abstracts, DoIS, eGranary Digital Library, INSPEC, Information Science & Technology Abstracts, LISA, PAIS, and other services.