Who will Interact with Whom? A Case-Study in Second Life Using Online Social Network and Location-Based Social Network Features to Predict Interactions between Users

摘要

Although considerable amount of work has been conducted recently of how to predict links between users in online social media, studies inducing features from different domain data are rare. In this paper we present the latest results of a project that studies the extent to which interactions - in our case directed and bi-directed message communication - between users in online social networks can be predicted by looking at features obtained from online and location-based social network data. To that end, we conducted a number of experiments on data obtained from the virtual world of Second Life. As our results reveal, location-based social network features outperform online social network features if we try to predict interactions between users. However, if we try to predict whether or not this communication was also reciprocal, we find that online social network features seem to be superior.