A Review of Humor for Computer Games: Play, Laugh and More
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Computer games are now becoming ways to communicate, teach, and influence attitudes and behavior. In this article, we address the role of humor in computer games, especially in support of serious purposes. We begin with a review of the main theories of humor, including superiority, incongruity, and relief. These theories and their interrelationships do well in helping us understand the humor process, but they have been developed in the context of traditional human activity. To explore how they relate to computer games, we present the findings of a qualitative study of player experience of humor and show how it relates to the theoretical perspectives. We then review the main functions of humor, especially its effects on social, emotional, and cognitive behavior. We show how each of these functions can be used in game design to support the specific experiences and outcomes of game-play. Finally, we address the issue of serious games and make suggestions on how humor can inform and support the design of those games. We suggest that humor can support design by smoothing and sustaining the game mechanics. Moreover, games can draw on the functions of humor in the real world for enhancing communication, learning, and social presence. Using humor makes games richer and more powerful, as well as fun.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it