Inferring personality of online gamers by fusing multiple-View predictions

Reliable personality prediction can have direct impact on many adaptive systems, such as targeted advertising, interface personalization and content customization. We propose an algorithm to infer a user's personality profile more reliably by fusing analytical predictions from multiple sources including behavioral traces, textual data, and social networking information. We applied and validated our approach using a real data set obtained from 1,040 World of Warcraft players. Besides behavioral and social networking information, we found that text analysis of character names yields the strongest personality cues.

Citation

Shen, J.; Brdiczka, O.; Ducheneaut, N.; Yee, N.; Begole, J. Inferring personality of online gamers by fusing multiple-view predictions. Twentieth International Conference on User Modeling, Adaptation and Personalization (UMAP 2012); 2012 July 16-20; Montreal, Canada. Berlin: Springer; 2012; LNCS vol. 7379: 261-273.