Automatic Classification and Rating of Videogames Based on Dialogues Transcript Files

Abstract

Video games industry represents one of the most profitable activity connected with entertainment and visual arts. Even more than movie industry, video game industry involves a great number of different professionals who work together to create products expected to reach people in many countries. A substantial part of these people are teenagers, strongly attracted and influenced by video games. For these reasons, various systems of labels have been created. They indicate the recommended age ranges for each product. These systems are based on different criteria, but they have in common the presence of descriptors, or labels, which identify the type of contents in the game. One of them is PEGI (Pan-European Game Information), and we will mainly take this system in consideration for the purposes of our study. The rating procedure includes questionnaire enquires compiled by the publisher for the automatic attribution of the label and a large process of manual control of each submitted game. In order to help this large and demanding process, we propose a system of video games rating based on automatic classification of the products performed over the “transcript” or script, files that display the full transcription of dialogues in a video game. The proposed automatic classification algorithm is based on large, specialized dictionaries. Such as the dictionary of offensive language. This is based on semantic vector spaces and on sentiment analysis, and is able to provide an age rating and a genre classification of video games. It works in a more efficient way in games with a consistent amount of dialogues. The experimentation of the proposed algorithm is returning encouraging results.

Alessandro Maisto edited Sect. 3, 4, 5, and 6; Giandomenico Martorelli edited Sect. 1 and 2; Antonietta Paone worked on data collection and dictionaries; Serena Pelosi edited Sect. 4.1.1.