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Discovering Social and Aesthetic Categories of Avatars: A Bottom-Up Artificial Intelligence Approach Using Image Clustering
Videogame avatars are more than visual artifacts-they express cultural norms and expectations from both the real world and the fictional world. In this paper, we describe how artificial intelligence clustering can automatically discover distinct characteristics of players' avatars without prior knowledge of a system's underlying data structures. Using only avatar images collected from a study with 191 players, we applied two clustering techniques-namely non-negative matrix factorization andfatcat:ufr2eohldfdwvox7gjvu3tzedy