Twitch.tv: The Communities We Make and the Language We Use
Faculty Mentor
Antonio M. Espinoza
Presentation Type
Poster
Start Date
5-8-2024 11:15 AM
End Date
5-8-2024 1:00 PM
Location
PUB NCR
Primary Discipline of Presentation
Computer Science
Abstract
in 2011 Twitch launched as an independent streaming platform before being acquired by Amazon in 2014. In its first year, twitch.tv achieved a viewership of 3.2 million users per month. Since then, Twitch has gone on to amass a monthly viewership of 240 million active users. Twitch is currently the defacto leader in the live streaming space, providing a large platform for content creators and content consumers to interact and collaborate. While Twitch was initially intended to cater to live gaming, its community has expanded their content to include topics e.g., ”just chatting”, political commentary, news, table top role playing games, etc. This produces a large amount of data that is organically organized by channels, their unique genres, and the viewers that contribute to their respective communities.
For future analysis, we introduce an infrastructure engineered to collect and parse Twitch chat in real time, as well as store pertinent information in a SQL database. The core of this system is a Python bot that leverages the Twitch API to monitor and collect chat messages across designated channels. After retrieval of the logs, the bot processes them, extracting key pieces of information, then sends them to a SQL database for storage. Although our projects goal is data collection, our hope is that this framework and the information it gathers will enable future analysis by researchers to extract meta-information about channels and their viewers to include general sentiment, political leanings, and speech patterns (both in individuals and communities).
Recommended Citation
Leachman, Eric M. and Espinoza, Antonio M., "Twitch.tv: The Communities We Make and the Language We Use" (2024). 2024 Symposium. 8.
https://dc.ewu.edu/srcw_2024/ps_2024/p2_2024/8
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Twitch.tv: The Communities We Make and the Language We Use
PUB NCR
in 2011 Twitch launched as an independent streaming platform before being acquired by Amazon in 2014. In its first year, twitch.tv achieved a viewership of 3.2 million users per month. Since then, Twitch has gone on to amass a monthly viewership of 240 million active users. Twitch is currently the defacto leader in the live streaming space, providing a large platform for content creators and content consumers to interact and collaborate. While Twitch was initially intended to cater to live gaming, its community has expanded their content to include topics e.g., ”just chatting”, political commentary, news, table top role playing games, etc. This produces a large amount of data that is organically organized by channels, their unique genres, and the viewers that contribute to their respective communities.
For future analysis, we introduce an infrastructure engineered to collect and parse Twitch chat in real time, as well as store pertinent information in a SQL database. The core of this system is a Python bot that leverages the Twitch API to monitor and collect chat messages across designated channels. After retrieval of the logs, the bot processes them, extracting key pieces of information, then sends them to a SQL database for storage. Although our projects goal is data collection, our hope is that this framework and the information it gathers will enable future analysis by researchers to extract meta-information about channels and their viewers to include general sentiment, political leanings, and speech patterns (both in individuals and communities).
