A method for longitudinal behavioral data collection in second life
Presence: Teleoperators and Virtual Environments
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
An Integrated Framework for Avatar Data Collection from the Virtual World
IEEE Intelligent Systems
Acquaintance or partner?: predicting partnership in online and location-based social networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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In this paper we present results of a study that aims to analyze publicly announced event data in the virtual world of Second Life with the goal to predict whether or not an event will be successful by terms of increasing the average traffic of a region. To that end, we collected in-world position data of avatars visiting events and data from the public accessible calendar of Second Life. Based on statistical analysis of features such as event category, duration, or maturity rating, provided by the Second Life event calendar, we built a simple predictive model that can decide upon the success of an event with an accuracy of over 92%.