  Nowadays, big effort is being put to study gamification and how game elements
can be used to engage players. In this scope, we believe there is a growing
need to explore the impact game mechanics have on the players' interactions and
perception. This work focuses on the application of game mechanics to lead
players to achieve certain types of social interaction (we named this type of
mechanics social interaction mechanics). A word matching game called CrossAnt
was modified so that it could dynamically generate different social interaction
mechanics. These mechanics consisted in different key combinations needed to
play the game and were aimed to promote what we think are three important types
of social interactions: cooperation, competition and individual exploration.
Our evaluation consisted on the execution of several sessions where two players
interacted with the game for several levels and had to find for themselves how
to perform the actions needed to succeed. While some of the levels required the
input from both players in order to be completed, others could be completed by
each player independently. Our results show that cooperation was perceived when
both players had to intervene to perform the game actions. However, longer
interactions may still be needed so that the other types of interactions are
promoted.

Human-Computer Interaction;Artificial Intelligence;Computers and Society