Abstract
Watching other people playing games on live streaming platforms have become more popular. In published literature, most of researches on live streaming focused on predicting the number of viewers in the live streaming period, explaining the high peak of the audience in a game, and finding out popular live streamers, and discussing usage behaviors such as exploring the gift giving. However, from available literature, relatively few works focus on discussing the text chats/comments which can affect other users’ watching behaviors. Therefore, this study aims to find important terms that affect viewing of live streaming. We used live game streaming as our study target. Using the comments of the audience in the chat room of the Twitch live streaming platform as experimental samples. Text mining and feature selection methods, including Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine-Recursive Feature (SVM-RFE) and chi-square test (χ^2 test), to find important terms that affect viewing of live streaming.
Published Version
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