Data Collection in Massively Multiplayer Online Games: Methods, Analytic Obstacles, and Case Studies

Abstract

Massively Multiplayer Online Games (MMOGs) occupy a unique position in the videogaming landscape. While multiplayer computer games are certainly not new (Spacewars, in 1962, was already designed for two players), MMOGs have gone much farther than any other genre in their attempts to encourage social interactions between large groups of players. This is all the more interesting when considering that most of the activities offered in a MMOG, such as killing monsters, leveling up a character, gaining more powerful abilities and gear, etc., are all already available in single-player games: from an individual standpoint, one could have a strikingly similar experience playing a MMOG like World of Warcraft (Blizzard, 2004), for instance, and a single-player role-playing game (RPG) like Dragon Age (Electronic Arts, 2009). Therefore, what makes MMOGs so unique and interesting is their social architecture: the way each game world is designed to maximize opportunities for player-to-player interactions. In turn, it is these repeated player interactions that keep subscribers coming back – and paying their monthly fee: as previous studies have shown “it is the players that are addictive [in MMOGs], not the game itself (Lazarro 2004).” Understanding the nature and structure of player behaviors and interactions in online games is therefore not only an interesting (and fun) sociological question: it is also potentially a very lucrative one, since a better understanding of player behavior could lead to improved social architectures with even higher attractiveness to the players and a corresponding increased retention (and profit).