Player Game Data Mining for Player Classification

• DOI: 10.22533/at.ed3921924055

• Palavras-chave: atena

• Keywords: game analytics, taxonomy of Bartle, classification of players, MMORPG, k-means

• Abstract:

  Analyzing and understanding the

  standard of players in virtual environments has

  been an activity increasingly used by digital

  game developers and producers. Players are

  the main reason that games are developed and

  knowing the main characteristics for each of your

  player is fundamental for game developers have

  a successful product. In the case of Massively

  Multiplayer Online Role Playing Games

  (“MMORPG”), the types of players vary, and, by

  classifying players’ behaviors, it is possible for

  developers to implement changes which satisfy

  players in targeted manners which may impact

  their level of interest and amount of time spent

  in the game environment. This study suggests

  that it is possible to identify and classify players

  via gameplay analysis by using consolidated

  theories such as Bartle’s archetypes or

  Marczewski’s types of players, which group

  players with the k-means algorithm. Below, is

  presented a dedicated section describing the

  Game Analytics processes and a session with

  the results obtained from the analysis of a

  specific guild from World of Warcraft.

• Número de páginas: 15