Introduction

This webtext is about seriality and serialization processes in games and gaming communities — and about the possible affordances of a digital humanities approach to studying these processes.

Seriality is, of course, a familiar feature of game franchises; Mario, Zelda, Pokemon, Tomb Raider, and the like are constituted not so much in games as in series of games, complete with sequels, spin-offs, tie-ins, and other forms of continuation. But beyond this more visible form of seriality, the serial character of games is operative on a number of other levels: it informs social processes of community-building among fans, while it also takes place at much lower levels in the repetition and variation that characterizes a series of game levels, for example, or in the modularized and recycled code of game engines.

In what follows, I want to consider how tools and methods of digital humanities — including so-called "distant reading" and visualization techniques — can shed light on these processes and provide a bridge between the various levels of seriality in digital games and gaming communities. The vibrant "modding" scene that has arisen around the classic Nintendo game Super Mario Bros. (1985) will serve as my case study. As I shall try to demonstrate, automated "reading" techniques allow us to survey a large collection of fan-based game modifications, while visualization software helps to bridge the gap between code and community, revealing otherwise invisible connections and patterns of seriality.

In addition to mounting this argument about "digital seriality" and the merits of a digital humanities approach to studying it, this webtext endeavors further to enable users to conduct their own experiments with data-driven research methods. Thus, under the "Tools" rubric on the navigation bar above, readers will find a number of interactive visualizations that can be used to locate patterns of serialization in a database of 200+ fan-made game mods. These visualizations, as I hope to demonstrate, are not merely "pretty pictures," and they should not be regarded as inert images that can at most communicate the results of previously conducted research; rather, they are tools in an emphatic sense: instruments of research. Together with the underlying data (also included here for users to work with in ways that might expand or challenge my findings), these visualizations can be employed for quasi-forensic purposes of discovery, comparison, correlation, and filtering, enabling insight into a large data-set and exposing the hidden connections between code and community.