Assessing Influential Users in Live Streaming Social Networks
|Abstract||Live streaming has risen to significant popularity in the recent past and largely this live streaming is a feature of existing social networks like Facebook, Instagram, and Snapchat. However, there does exist at least one social network entirely devoted to live streaming, and specifically the live streaming of video games, Twitch. This social network is unique for a number of reasons, not least because of its hyper-focus on live content and this uniqueness has challenges for social media researchers.
Despite this uniqueness, almost no scientific work has been performed on this public social network. Thus, it is unclear what user interaction features present on other social networks exist on Twitch. Investigating the interactions between us... (more)
|Contributor||Jones, Isaac (Author) / Liu, Huan (Advisor) / Maciejewski, Ross (Committee member) / Shakarian, Paulo (Committee member) / Agarwal, Nitin (Committee member) / Arizona State University (Publisher)|
|Subject||Computer science / Data Mining / Data Science / Influence / Machine Learning / Social Media / Twitch|
|Note||Doctoral Dissertation Computer Science 2019|
|Collaborating Institutions||Graduate College / ASU Library|
|Additional Formats||MODS / OAI Dublin Core / RIS|