Twitch Analytics With Sentiment Mining

Twitch Analytics With Sentiment Mining

Overview Launched in 2011, Twitch is an interactive live-streaming platform for content creators and spectators who participate via online chat. Streams can vary from a few minutes to several hours (in the case of epic gameplay sessions). In this blog, get an inside view of why sentiment analysis is important for Twitch Advertisement and how to plan your Twitch ad campaigns with semantic customer insights.

Who Advertises on Twitch?

Twitch is not like other social media platforms. Although it’s owned by Amazon, it retains an edge as most of its users are tech-savvy gamers. These people are typically used to high levels of interactivity and love sharing their experiences.

Users skew heavily male (65%) and young (41% are aged 16-24 and 32% are 25-34).

Given the demographics, it’s not a surprise to learn that B2C companies that sell apps and games, gaming tech, fast food, beverages, and workstations, dominate when it comes to advertising. Top advertisers include Ubisoft, EA, KFC, Hershey’s, Red Bull, and Guess.

Guess’s a collaboration with key influencer Adelaide Kane is a rare example of a brand leveraging the female minority using the site. That said, Kane has over 2 million followers on Twitter, so Guess clearly saw a cross-platform opportunity to link their fashion label with this influential young star.

How is Sentiment Analysis done on Twitch?

From what Data Sources Can I Obtain Customer Insights on Twitch?

Live streams, chat content, and channel information can all be mined for customer insights using a sentiment analysis platform. Twitch has an API for this too. Using Python or a similar language, code can be constructed to pull together data from relevant tags. Let’s break down what information you can get from the three main data sources.

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Live Streams (audio and video) With video and audio content analysis, it is possible to read emotional responses from Twitch users, as well as transcribe and analyze spoken utterances. By leveraging this information, you can gain access to the unfiltered, in-the-moment responses of Twitch streamers.

Chat On Twitch, a sentiment analysis solution must be particularly sophisticated in its semantic breakdowns to analyze and understand chat comments.

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