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Playing to Win? Measuring Social Interaction in Games
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Playing to Win? Measuring Social Interaction in Games


January 24, 2012 Article Start Previous Page 2 of 3 Next
 

Measuring Social Interaction

To understand how social interaction differs across player types, and to show the application of the methodology for measuring social interaction, we ran eight lab sessions, each with two collocated players, 30 minutes of playtime, and triangulated social interaction, biometric, and player interview data to gain a better understanding of the forms, and effects, of social interaction during gameplay.

The players were picked from pre-existing social groups to encourage interaction. Pairs of players were asked to play a game of Buzz! Quiz World, the social quiz game created by Relentless Software.

During these sessions, a custom tool, created in Processing, was used to record the forms of social interaction noted, and automatically timestamp the data for further analysis.

Throughout the session GSR (galvanic skin response) data was taken, measuring how their body reacted to the in-game events and the forms of social interaction noted.

GSR has a linear correlation with arousal (such as excitement or frustration) and reflects non-specific emotional response. The GSR data was presented on a timeline, and was later correlated with the social interaction data.

After the session, players were asked to record their experience on blank graph paper, and annotate this. This was done unprompted, before interviewing the players, to ensure that a fair representation of their memories of the session, and the events/interaction that occurred during it, could be evaluated.


The custom social interaction recording tool

The players were then interviewed while watching a video of their play session in order to gain an understanding of what they were thinking throughout the session. When prompted by peaks in the GSR signal or a-typical social interaction behavior, the players were asked to describe what they were thinking or doing at that moment. This gave increased insight into why players were acting as they were, not just how they acted.


A player's self-assessed "experience" graph

What Did We Find?

As mentioned, we broke the results down by the four player types, to gain greater insight into the motivations behind each form of interaction noted.

Killers

Killers, who as we noted are most interested in defeating other players, showed the highest degree of the "trash talk" behavior, insulting and goading their opponent.

It was also interesting to note that Killers' levels of arousal, as identified by GSR, and social interaction, dropped significantly when it was obvious they were going to win -- they are only interested in "worthy" opponents, as was confirmed later by the interviews.


A Killer's self assessed "experience" graph

Recommendations:

Their desire for defeating other players could be realized and emphasized in game through the introduction of taunt mechanics in games, as are found in many fighters.

Game mechanics can be introduced to ensure continued engagement by ensuring that all players always have the opportunity to win. This has previously been seen through the rubber banding in games such as Mario Kart, or the final round of Buzz! Quiz World, which converts the score players have earned throughout the game into a head start in the last round.


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