Proceedings of the First ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play 2014
DOI: 10.1145/2658537.2661306
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Intangle

Abstract: Multi-player computer games are increasingly being designed to engage with interpersonal bodily interactions, however, their focus is often limited to facilitating direct body contact. In contrast, we propose that designers foster varying levels of body contact through the design of shared controller interactions to introduce new types of gameplay that affords players a more nuanced engagement with the concept of socially and personally mediated body-space in games. We explore this through our game intangle, w… Show more

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Cited by 14 publications
(3 citation statements)
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References 8 publications
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“…This facilitates closeness and touch, as described in previous work around game input. Garner et al's intangle game, for example, is designed around shared controllers and gameplay that strongly facilitates physical closeness [2]. Similarly, Touchomatic by Marshall and Tennent is an arcade that incorporates physical touch between players as a game input [6].…”
Section: Related Workmentioning
confidence: 99%
“…This facilitates closeness and touch, as described in previous work around game input. Garner et al's intangle game, for example, is designed around shared controllers and gameplay that strongly facilitates physical closeness [2]. Similarly, Touchomatic by Marshall and Tennent is an arcade that incorporates physical touch between players as a game input [6].…”
Section: Related Workmentioning
confidence: 99%
“…, encourages people to brutally force opposing players to move. B.U.T.T.O.N [41] gives players instructions such as 'the last player to let go of their controller button wins', designed to encourage players to use imaginative 'Brutally Unfair Tactics' for example to grab controllers off other players; similarly Intangle [13] uses shared controllers and instructions which encourage physical social interactions between players.…”
Section: Balance Of Power [25]mentioning
confidence: 99%
“…This gave us a set of 347 videos in which gameplay and players are visible. We also annotated each video with estimated demographic data, including a) estimated age for each player, as child (<12), teen (12)(13)(14)(15)(16)(17)(18)(19)(20), or adult (20+), and b) presenting gender of each player, male / female / uncertain.…”
Section: Dataset Processing and Analysismentioning
confidence: 99%