Personalized game reviews

Abstract

One way of subjective evaluation of games is through game reviews. These are critical analyses, aiming to give information about the quality of the games. While the experience of playing a game is inherently personal and different for each player, current approaches to the evaluation of this experience do not take into account the individual characteristics of each player. We firmly believe game review scores should take into account the personality of the player. To verify this, we created a game review score system, using multiple machine learning algorithms, that computes multiple review scores for different personalities which allow us to provide a more holistic perspective of this value, based on multiple and distinct player profiles. Our results support that the approach is statistically and significantly better than using the weighted average score provided by metacritic.com, currently one of the most popular websites that aggregate video game reviews, among other media products.