Abstract
In this work, the team formation process in an online game was formulated as a sign prediction problem of social networks. Depending on the participation in either collaborative or competitive teams and squads and four different interaction types among gamers, the objective was to predict the signs (positive/negative) of their interactions in colluding or competing teams. Temporal features pertaining to the factors affecting team formation were used in a supervised classification setup. High performance by a classifier denotes that historical information related to gamers’ prior interactions are effective in predicting the sign of their interactions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.