Title

Mining Social Interaction Data In Virtual Worlds

Keywords

Community Detection; Longitudinal Analysis; Network Text Analysis; Virtual Worlds

Abstract

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.

Publication Date

1-1-2014

Publication Title

Communications in Computer and Information Science

Volume

498

Number of Pages

86-105

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-662-46241-6_8

Socpus ID

84922816447 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84922816447

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