Automatic Identification of Video Game Development Problems using Word Embedding and Ensemble Classifiers

Abstract

The video game development industry, also known as the interactive entertainment business, is involved in building, marketing, advertising, and monetizing video games. Over the last few years, this industry has come into the mainstream from initially being in the focused market. The growing video gamer demographic has increased by video game development methods and techniques. A postmortem of a video game is a close examination of the video game’s development phase and an analysis of what went right or wrong with the video game. Unfortunately, since there is not much understanding regarding the challenges encountered by programmers, there is a lack of trustworthiness primarily because postmortems lack a proper structure and are informally written. In this work, with the help of word embeddings and ensemble machine learning classifiers, a systematic analysis is performed on various technical and non-technical issues faced by the video game industry. It is believed that automation and machine learning classifiers could aid game developers in identifying what problem they are facing, given the quote (description), and thus be able to figure out a solution quickly. Frequently committed mistakes could be identified and avoided, and this work could act as a starting point to further consider software development and video game development in the same context.