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Playing to Win? Measuring Social Interaction in Games
 
 
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  Playing to Win? Measuring Social Interaction in Games
by Steve Bromley, Graham McAllister, Pejman Mirza-Babaei, Jonathan Napier [Game Design]
5 comments Share on Twitter Share on Facebook RSS
 
 
January 24, 2012 Article Start Page 1 of 3 Next
 

[Usability and user experience studio Vertical Slice and developer Relentless Software have collaborated on a study to discover what it is that turns friends against each other in games, through understanding how player types affect the forms of social interaction found in collocated (same room) multiplayer games and what this means for developers.]

Why is Social Interaction Important?

Social interaction is becoming an increasingly important theme in multiplayer gaming. The success of the Wii, and its focus on casual multiplayer games such as Wii Sports or Just Dance, has highlighted how important playing with friends is to reaching wider audiences and creating successful game experiences.


For developers, it's therefore important to be able to understand the types of social interaction that exist, and measure them during the development of games. In a collaboration between Relentless Software and Vertical Slice, we have been developing a methodology to allow developers to evaluate interaction from the very earliest prototypes.

This not only allows developers to measure the forms of interaction evident in their game but also, through increasing our ability to profile players, allows developers to target games towards specific gamer types.

Understanding Social Interaction

In order to measure social interaction, it is first important to define the types of interaction that occur during multiplayer collocated (i.e. sat in the same room) gaming.

Voida, Carpendale, and Greenberg, in their paper The Individual and the Group in Console Gaming, observed people playing multiplayer social games such as Guitar Hero, Mario Party and Mario Kart. By noting and defining the forms of behavior evident in these sessions, they categorized interaction into six groups, presented below. Ackermann also conducted a study, coding and analyzing the forms of interaction noted by players at LAN parties, and noted similar interaction categories.

By combining their research with data from previous Relentless Software usability tests, the following categories of interaction were defined:

Voida et al.'s Original Category

Revised Social Interaction Category

Description

Constructing Shared Awareness

Shared Awareness

Shared Awareness includes building a shared awareness of the game state, and can include collaborative working out, giving hints, or making another player aware of something within the game, such as game mechanics or "what to do". It can also include reporting to other players what activities you are performing within the game.

"Let me have the health pack, I'm low on health"

Requesting Information

Requesting Information typically includes asking about what is happening in game, how the game works, or how to achieve their goal. It can also include asking other players to report their status. It is often combined with a period of shared awareness.

"How do I solve this puzzle?"

Reinforcing Shared History

Shared History

Shared History includes discussing what happened earlier in the game, or in a prior play session. May include links to other games, or with players not present.

"Remember when we beat that boss?"

Sharing in Success and Failure

Shared Success

Shared Success includes celebrating a group success, or congratulating another player on their success. It can include a group celebration despite being in a competitive situation.

"Well done, that was really hard!"

Shared Failure

Shared Failure includes taking group responsibility for failing a task, offering reassurance, or commiserating with a player who has failed a task. It does not include blame (which may be more appropriate under Trash Talk).

"It's not your fault, it was a difficult question!"

Engaging in Interdependence and Self-Sacrifice

Team Optimization

Team Optimization includes discussing the group dynamics, or negotiating an individual's contribution to the group. It can include assessing the ability of others, and discussions over who is leading or in control. Can also include denying players the chance to join in.

"Let me do this bit, I'm better at math!"

Talking Trash

Trash Talk

Trash Talk includes celebrating your own success over the other players, or laughing at their failure. This can be in competitive or collaborative game types, and often involves put downs or insults.

"You suck!"

Falling Prey to the computer's holding power

Self Indulgence

Self Indulgence includes not playing the game at the expense of other players' enjoyment, making up one's own meta-game, or not participating fully, leading to a disruption of the flow of the game. It can include repeatedly performing the same action (i.e. viewing a hidden in-game feature or Easter egg).

"My character's going to have a nap now."

N/A

Off Topic

Off Topic includes discussing non-game based interaction or discussion

"Nice weather we're having!"

Bart Stewart recently discussed the use of models for player types, and noted that the most popular model from Bartle divides players into four types, as follows. We have also used the same idea of player types as a way to distinguish between each player's individual motivations.

Player Type

Description

Killers (Clubs)

Killers are interested in combat/competition with other human players, and prefer this over interaction with non-player characters.

Achiever (Diamonds)

Achievers are most interested in gaining points or alternative in-game measurements of success. These players will often go out of their way to gain items that have no in-game benefit besides prestige, such as Achievements' or Trophies.

Explorer (Spades)

These players are interested in discovering the breadth of a game, and will explore new areas or take non-optimal routes to explore. They do not like time limits, since this limits the potential to explore options.

Socializers (Hearts)

These players are interested in the social aspect of game play, rather than the game itself. They enjoy interacting with other players, and use the game primarily as a means of communication.

In Bartle's theory, each individual player's motivation stretches across each group, with a player being scored in each category, i.e. 80 percent killer, 10 percent socializer, 10 percent achiever.

For this study, the online Bartle Test was utilized, which asks the user 30 questions, before giving them a Bartle player type. For analysis of the results, we divided players by their type.

 
Article Start Page 1 of 3 Next
 
Comments

E McNeill
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Is there any more GSR data to share? Did it correspond with your predictions or the players' self-reports?

Pejman Mirza-Babaei
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Thanks for the comment. Yes, we have more data. In fact the extended version of this article will be appear as a book chapter (book title: Social Aspects of Digital Gaming) later this year, which will include more data on GSR, etc. I will keep you posted on this if you are interested.

Samuel Green
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Interesting use of a trivia game as the testing game. As a killer myself, I would argue that a trivia/knowledge based game is a poor choice to test killers. In a game of skill (RTS or FPS for example), I will compete no matter how inexperienced I am. I'm a killer! I rock at these games (at least I perceive that I do)! In a trivia game, even as a killer, I will tend to not have that killer instinct if...

a) The area of questioning is outside of my experience
b) I don't physically beat people with skill

Knowledge is useful in games (DotA for example requires an encyclopedia's worth of knowledge) but what appeals to me most as a killer is the competition of skill and strategy, none of which are parts of a trivia game. It's the reason I don't enter Pub Quizzes.

Bart Stewart
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This seems like a very good starting point for research into an aspect of gaming that could benefit from being better understood with objective data. Why *do* people play together? What do they get out of it? How do those interactions succeed or fail?

I look forward to the book! :)

Regarding the classification scheme proposed, are any of the authors familiar with the "Six Thinking Hats" model of collaborative discussion described by Edward de Bono?

I thought a number of the classifications for social behavior in games seemed analogous to the six "hats" styles:

INFORMATION GATHERING
Shared History -- Red Hat of feelings and personal views of data
Requesting Information -- White Hat of objective data: facts, numbers

INFORMATION ANALYSIS
Shared Success -- Yellow Hat of optimistic understanding, opportunities
Shared Failure -- Black Hat of pessimistic understanding, risks, constraints

INFORMATION MANAGEMENT
Shared Awareness -- Green Hat of creative idea generation
Team Optimization -- Blue Hat of collaborative process control

Both of these are systems for explaining how people communicate with each other toward achieving a common goal (even if that goal makes them antagonists in a game, they're still agreeing to play the same game). So I'd actually be more surprised if there didn't appear to be some similarities in the descriptions of how people interact.

As there do seem to be some strong associations, I wonder if closer study of de Bono's Six Hats model might yield some useful insights into how gamers interact.

Steve Bromley
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That's a great point Bart. I'd be tempted to say that these methods of interaction are universal, rather than being specific to gaming, and match with those identified by de Bono's 6 "hats".

It's also interesting to note research where Bartle's player types have also been independently derived from non-game studies, implying that a lot of games user research is actually related to universal behaviour, with very few idiosyncrasies related only to gaming.

Lots of potential here for further research in the future!


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