The variable 'genre' aims to identify and compare different types of games, mainly in terms of gameplay differences (i.e., rules and players’ possibilities to interact with a game). Genre is usually coded by using external video game databases, such as those published on journalistic websites.
Field of application/theoretical foundation:
The variable ‘genre’ is often used in content analyses of video games to identify and compare different types of games. Lynch et al (2016), for example, investigate whether the number of sexualized characters differ between various video game genres (Action, Adventure, Fighting, Platformer, Role-Playing-Game, Shooter). However, the definition and validity of different genre lists is controversially discussed in the literature (e.g., Arsenault, 2009).
Most content analytic studies adopt the value of the genre variable for a given game from an external source. Most commonly, scholars use one or more databases published on journalistic video game websites (www.ign.com; www.gamespot.com; www.giantbomb.com), on Wikipedia or the database of the Entertainment Software Rating Board (www.esrb.org). Most of the genre classifications in these databases are based on gameplay characteristics rather than narrative themes. For example, both the game Starcraft as well as Anno 1602 are classified as ‘real-time strategy’ on Wikipedia, regardless of the fact that they have rather different settings (science fiction vs. historic).
To ensure that games are classified into a few, clear genre categories (some journalistic genre lists are extremely detailed, see Arsenault, 2009), many content analyses define potential values of the genre variable in a first step (see below). For example, while IGN (www.ign.com) currently categorizes games in 27 different genre categories, studies mostly only differentiate between 9-15 genres (see below). In a second step, the appropriate value of the variable for a given game is coded based on the external sources. Additionally, rules need to be developed that determine how to deal with potential conflicts. At first, if coding is based on multiple sources, it needs to be decided how to deal with potential conflicts between these sources. For example, Hanninger and Thompson (2004) report that “the genre most frequently used” (p. 867) was coded in such cases. In contrast, Lynch and colleagues (2016) prioritized entries in the IGN database and only used additional sources (GiantBomb and Wikipedia) if information was lacking. Moreover, scholars need to decide how to deal with multiple categorizations of a given game in the same database (e.g. Anno 1602 is classified as ‘real-time strategy’ and ‘city-building game’ on Wikipedia). Lynch and colleagues (2016), for instance, coded the first genre from their list which was mentioned in the database. Finally, scholars must also ensure that their shortened list of genres (step 1) is consistent with the potentially more detailed classification approach of external databases or develop a scheme that defines the correspondence between these lists.
References/combination with other methods of data collection:
Scholars may also use survey methods to classify games in homogeneous groups. For example, experts or players could be asked to evaluate several games on multiple dimensions, such as setting and gameplay mechanics. Subsequent statistical cluster analysis (e.g., hierarchical clustering) could be applied to identify homogeneous groups of games. Moreover, games could be clustered on the basis of their textual descriptions, for example, in Wikipedia articles. Automated methods, such as latent semantic analysis, can be used for this purpose (e.g. Ryan et al., 2015).
Example studies
Coding material
Measure
Operationalization
Unit(s) of analysis
Source(s) (reported reliability of coding)
Entry of a game in the video game database published on the journalistic website IGN; if information was unavailable the website GiantBomb as well as Wikipedia were used
Genre
Predefined list of genres: “action, adventure, casual, children’s entertainment, family entertainment, fighting, flight simulation, horror, platformer, racing, role-playing game (RPG), shooter, sports, strategy, or other/indeterminable” (p. 562)
Game
Lynch et al., 2016 (reliability not stated)
Entry of a game in video game databases published on journalistic websites (IGN, GameSpot, GameFAQs) and the database of the Entertainment Software Rating Board
Genre
Predefined list of genres: “action, adventure, fighting, racing, role-playing, shooting, simulation, sports, strategy, or trivia” (p. 857)
Game
Haninger & Thompson, 2004 (reliability not stated)
Entry of a game in the video game database of the Entertainment Software Rating Board
Genre
Predefined list of genres: “adventure, flight simulator, fighting, music, role-playing, racing, shooter, sports, or strategy/puzzle” (p. 65)
Game
Smith, Lachlan, & Tamborini, 2003 (reliability not stated)
References
Arsenault, D. (2009). Video Game Genre, Evolution and Innovation. Eludamos. Journal for Computer Game Culture, 3(2), 29.
Haninger, K., & Thompson, K. M. (2004). Content and ratings of teen-rated video games. JAMA: The Journal of the American Medical Association, 160(4), 402–410. https://doi.org/10.1001/archpedi.160.4.402
Lynch, T., Tompkins, J. E., van Driel, I. I., & Fritz, N. (2016). Sexy, Strong, and Secondary: A Content Analysis of Female Characters in Video Games across 31 Years. Journal of Communication, 66(4), 564–584. https://doi.org/10.1111/jcom.12237
Ryan, J. O., Kaltman, E., Mateas, M., & Wardrip-Fruin, N. (2015). What We Talk About When We Talk About Games: Bottom-Up Game Studies Using Natural Language Processing. Proceedings of the 10th International Conference on the Foundations of Digital Games, 10.
Smith, S. L., Lachlan, K. A., & Tamborini, R. (2003). Popular video games: Quantifying the presentation of violence and its context. Journal of Broadcasting & Electronic Media, 47(1), 58–76. https://doi.org/10.1207/s15506878jobem4701_4
Learning in Real-Time Search: A Unifying Framework
