Title: Setting Players' Behaviors in World of Warcraft through Semi-Supervised Learning,
Abstract: Digital games are one of the major and most important fields on the
entertainment domain, which also involves cinema and music. Numerous attempts
have been done to improve the quality of the games including more realistic
artistic production and computer science. Assessing the player's behavior, a
task known as player modeling, is currently the need of the hour which leads to
possible improvements in terms of: (i) better game interaction experience, (ii)
better exploitation of the relationship between players, and (iii)
increasing/maintaining the number of players interested in the game. In this
paper we model players using the basic four behaviors proposed in
\cite{BartleArtigo}, namely: achiever, explorer, socializer and killer. Our
analysis is carried out using data obtained from the game "World of Warcraft"
over 3 years (2006 $-$ 2009). We employ a semi-supervised learning technique in
order to find out characteristics that possibly impact player's behavior.