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Mining TV Twitter Networks for Adaptive Content Navigation and Community Awareness

Publication Type: 
Refereed Conference Meeting Proceeding
In this work, we explore the potential of mining social media streams for extracting collective knowledge related to television (TV) programming. We pro- pose to provide near real-time online community awareness around a set of current TV shows being broadcasted, as well as an adaptive content navigation experience purely based on automatically updated social relatedness, to enhance the online tele- vision services and support the characteristics of modern television viewers. As an example, we take the case study put forth by Raidió Teilifís Éireann (RTÉ), the na- tional public television and radio provider of Ireland. RTÉ also streams its content online and has a strong presence in the Twitter micro-blogging service. To support end-users in exploring the RTÉ catalog and understand what is happening in Twitter related to its programming, we developed the RTÉ XPLORER prototype. By using Adaptive Content Navigation and Community Awareness services, we aim for users to find interesting content faster and participate in an enhanced/richer social expe- rience around their favorite shows. The main contributions of this paper include an analysis of captured Twitter data, an in-detail description of the RTÉ XPLORER and the presentation of a functional prototype that showcases our system within the existing RTÉ streaming service.
Conference Name: 
BCS SGAI Workshop on Data Stream Mining Techniques and Applications, AI-2016 Thirty-sixth SGAI International Conference on Artificial Intelligence
Digital Object Identifer (DOI): 
Publication Date: 
Conference Location: 
United Kingdom (excluding Northern Ireland)
National University of Ireland, Galway (NUIG)
Project Acknowledges: 
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