We talk about some preliminary work correlating pro-social behaviors in a popular first-person shooter game with other player retention and engagement metrics.

1. Revival Actions in a
Shooter Game
Sauvik Das1
,Thomas Zimmermann2
, Nachiappan
Nagappan2
, Bruce Phillips2
, Chuck Harrison2
2
Microsoft Corporation
{tzimmer, nachin, bruce.phillips, charlesh}
@microsoft.com
1
Carnegie Mellon University
sauvik@cmu.edu

2. Motivation
• There is a growing interest in
understanding social behavior in games.
• How does social behavior associate with
more traditional shooter game metrics?

3. The Game
• A popular multiplayer third-person shooter
game.
• Online team-based multiplayer
component.
• Two teams, playing against each other.

4. The Game
• Social play can be operationalized as:
• Revivals
• Assists
• Sharing weapons/ammo
• Spot/mark enemies

5. The Game
• Social play can be operationalized as:
• Revivals
• Assists
• Sharing weapons/ammo
• Spot/mark enemies

6. The Data
• Random sample of 26,000 players.
• Play traces of 928,000 cumulative
multiplayer sessions played.

7. Method
• Separated players into two groups:
• Group A: Never revived any teammates
• Group B: Revived a teammate at least
once.

8. Dimenson Characteristic Change
Engagement Session Count +297%
Skill
Kills +100%
Killing during
execution
+195%
Was Revived -55%
Deaths -12%
Success Win Rate +19%
Social Gave Weapon +486%

9. Preliminary Result
• Players who exhibit “pro” social behavior
appear to have a better experience with
the game

10. Future Work
• Extricate independent social dimensions.
• Analyze impact of social behavior across
three lenses:
• player’s social behavior
• team’s social behavior
• enemy’s social behavior (among
themselves)

11. ?

12. Future Work
• Specific focus on retention.
• Strategy:
• cluster players according to social
dimensions (self, team, enemy)
• comparative analyses of cluster centroids.
• survival analysis for different clusters.