Developing Analysis Methods for Real-time Chats in Game Play Streams
Leader: Raine Koskimaa, Jyväskylä University, Collaborators: UEF, TAU
The foreseen impact is to develop analysis methods for real-time chat in game play streams. One of the biggest transformations across contemporary media cultures is the proliferation of streamed audio-visual content with textual communication features. Online streams of both amateurs and professionals are changing the ways through which people engage with the world. While online streams have been studied increasingly over the past years, the employed methods we currently have are typically qualitative or (if quantitative) lack the means for processing larger amounts of content. Thus, we need tools to study online streams quantitatively, for instance, to enable even thousands of hours in genre-profiling analyses. We will deliver machine learning tools to analyse interactions between audio-visual and textual communication. Work in this WP will be carried on by the CoE in Game Culture Studies JYU team, which has already done significant work on analyzing discussions in game streams, and the TAU machine learning team of the CoE having worked on gaming social media analytics.