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What are the challenges of creating live-stream content?

Scholarly Critique #3.2

Authored by: Daniel Farrington & Nicholas Muesch

Worcester Polytechnic Institute

March 2015

This resource for this scholarly critique was found during recent Google Scholar searches for “Twitch” and “live-streaming”. The authors designed this project to analyze the content of Twitch and gather the opinions of it’s users “through three primary tools: A Web crawler, which gathers stream metadata, a survey, which gathers YouTube and Twitch user demographics, preferences, and opinions, and a third-party Website, which gathers stream technical data” (p.1). The Twitch platform is also compared to YouTube to provide some context for the findings that are discussed. The motivation for this study is for the results to “aid in the development of future live-streaming platforms” (p. 1).

One aspect of this research I appreciate is the broad approach taken by the authors to outline how live-streaming fits into the world of video content, and provide a solid foundation for the connection to Web 2.0 practices. From the perspective of an individual or organization that is looking for new ways to connect with an audience it’s important to provide a holistic perspective. For those interested in becoming a broadcaster, the correlation between stream audio and video quality and channel popularity could help new broadcasters make informed decisions.

Their methodology was designed to generate a large amount of quantitative data on the technical aspects of content creation and consumption of content. This is accomplished through the use of mostly automated processes, including a data “scraper” and a “stream analyzer”. These processes allow for the collection data from a significant sample size, increasing the credibility and validity of the technical data. Some data collected was similar to other data sources available on quantcast and, for example the gender breakdown of Twitch users. The practice of data collection at particular times of day based on average level of users was also of note.

I also appreciate the author’s suggestions for future work based on this study. For those who might be interested in developing their own live-stream video platform, the authors suggest that “information on Twitch content may allow companies to understand what they can expect in terms of network traffic and hardware requirements, especially storage space, and also to understand what users expect from a competent service, and what features should be implemented” p. 6.

This study was interesting to compare with my own research due to the significant different in how data was collected and analyzed. My research relies more heavily on quantitative data, and has a much smaller sample size. However there were some parallels between what has emerged in my findings in connection with their findings. For example, based on the findings of my research, one of the most significant challenges of creative engagement on Twitch as a broadcaster was getting started and growing your stream. The findings from this research provided some very straightforward information on the most common audio and video settings for popular streams. The combination of both our findings reveals a potential opportunity to create resources and support for aspiring broadcasters.

There were few elements of this research that I felt needed development. Minimal research was referenced in the literature review, and while I understand this challenge due to my own frustration finding Twitch related resources, there are other types of resources that could be noted in relation to the major themes of the work. Other than the development of the literature review, some charts were a bit challenging to understand and need some revision.

My biggest question after reading this report relates to wondering what types of support resources are available for beginning broadcasters on Twitch. What programs are available to help broacasters promote their channels? I look forward to learning more about this learning niche.

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