Natural Language Processing in Game Studies Research: An Overview

Natural language processing (NLP) is a field of computer science and linguistics devoted to creating computer systems that use human (natural) language as input and/or output. The authors propose that NLP can also be used for game studies research. In this article, the authors provide an overview of NLP and describe some research possibilities that can be explored using NLP tools and techniques. The authors discuss these techniques by performing three different types of NLP analyses of a significant corpus of online videogame reviews: (a) By using techniques such as word and syllable counting, the authors analyze the readability of professionally written game reviews, finding that, across a variety of indicators, game reviews are written for a secondary education reading level; (b) the authors analyze hundreds of thousands of user-submitted game reviews using part-of-speech tagging, parsing, and clustering to examine how gameplay is described. The findings of this study in this area highlight the primary aesthetics elements of gameplay according to the general public of game players; and (c) the authors show how sentiment analysis, or the classification of opinions and feelings based on the words used in a text and the relationship between those words, can be used to explore the circumstances in which certain negatively charged words may be used positively and for what reasons in the domain of videogames. The authors conclude with ideas for future research, including how NLP can be used to complement other avenues of inquiry.