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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Mining Social Interaction Data in Virtual Worlds
verfasst von : Syed Fahad Allam Shah, Gita Sukthankar
Erschienen in: Agent Technology for Intelligent Mobile Services and Smart Societies
Verlag: Springer Berlin Heidelberg
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Virtual worlds and massively multi-player online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. However these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms. This chapter presents techniques for inferring the existence of social links from unstructured conversational data collected from groups of participants in the Second Life virtual world.