14 September 2011

The aesthetics of gameplay: a lexical approach

The aesthetics of gameplay: a lexical approach
Zagal and Tomuro

See the PDF or the ACM page.

Primary Elements of Gameplay Aesthetics
Aesthetics cluster Words in cluster Description
Pacing fast, stressful, dull, tedious The perception of how often game events occur.
Scope endless, vast, immense, minimal The size of the possibility space afforded by a game.
Complexity simple, short, complex, uncomplicated The measure, or sense, of the number of parts in a system and how they are interrelated.
Demands hardcore, experienced, retro, demanding The requirements imposed upon the player by the gameplay
Cognitive Accessibility deep, unusual, twisted, intricate, The measure, or sense, of the opacity of a system and the challenges it poses in understanding it.
Impact addictive, boring, overwhelming, visceral What we feel games “do to us” when we play them, and how they make us feel.
  • Analyzed nearly 400k user reviews posted before April 2009 on gamespot.com. 8k games covered by reviews from 112k users.
  • 40% of user reviews contain the word gameplay
  • Method: Stanford Parser to perform part-of-speech tagging. Matrix of (723 adjectives total that precede and modify the word gameplay) x (5000 most frequent words that occur before or after the adjective, ie context words, ie words that give a context to the adjective). Cells of the matrix contain number of occurrence of an adjective with a context word. Run kmeans on the matrix to obtain k=30 adjective clusters. (Compared to k=10 or 20, k=30 generated better-looking clusters). Two adjectives are similar (and put in the same cluster) if their context word distributions are similar. Then, give a name to each cluster based on the adjectives it contains.
  • Only 2 clusters about narrative elements. Therefore, players have no difficulties separating the formal or mechanical aspects (game mechanics) from their narrative interpretations (representation).
  • AI does not emerge as a cluster. Possible reasons: no language to describe game AI, or games AI are not sophisticated enough, or a too recently marketed topic to feature in reviews.
  • Genre does not emerge as a cluster.
  • Limitations: Gamespot population = 95% males, lots of colloquial words disappeared in cleaning phases.

My remarks

  • A group like "fast FPS gameplay" may have been considered as "fast gameplay" because FPS is not an English adjective, and the Stanford parser only looks at English adjectives. Since genre adjectives are not English but rather specific of gamer communities (e.g. "FPS", "RTS", "JRPG", etc.), genre did not appear in clusters.
  • It'd be interesting to know which game names occurred most often next to gameplay. For instance, "gameplay like Civilization" may be quite rare, but very meaningful when talking about a niche genre.
  • If genre is a label of the dataset, then it could be interesting to cluster a matrix like adjectives x genre. Goal = see which adjectives are explaining most a genre.

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