Using Big Data Tools and Techniques to Study a Gamer Community: Technical, Epistemological, and Ethical Problems

Authors

  • Maude Bonenfant Université du Québec à Montréal
  • Fabien Richert Université du Québec à Montréal
  • Patrick Deslauriers Université du Québec à Montréal

Abstract

This paper discusses an exploratory approach taken by researchers in the fields of semiotics and communications in order to not only share a specific research experience, but also help build a research sector that combines game analytics with social sciences. The main objective of our research was to define parameters of digital identity within the framework of the study of an online video game player community. To this end, we examined several constitutive elements of digital identity, namely the effects of the “avatar” apparatus on the identity of users, online interactions, and the meaning of “living together” in the digital world. We used both qualitative and quantitative methodologies: a semiotic analysis of the game, a discursive analysis of the forum, semi-structured interviews, and an automated analysis of big data sets. In this paper we will focus on the automated analysis of big data sets, addressing two key points: the working method developed by the research team, and the achievement of the research objectives by merging quantitative and qualitative perspectives together. Following a summary of the research approach, this article will present the methodological, epistemological, and ethical difficulties that may be encountered in studying a player community with this type of research approach.

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Published

2017-02-05