Game analytics and player psychology: creating reliable models of player motivation

动机可以粗略地定义为大脑和思维的过程，能够驱动和深刻塑造人类的行为。激励过程嵌入到许多日常生活情景中，通过广泛的激励机制和对象发挥作用。然而，在视频游戏环境中理解这一过程需要更全面的方法，不仅要考虑游戏的激励属性，还要考虑玩家的个人特征。我的项目旨在创建可靠的跨游戏玩家动机模型，并考虑到自然的个体间变异性的贡献。这将通过一种混合方法将游戏中的行为数据和心理模型联系起来，其中来自(假设驱动的)小规模实验研究的结果将指导实现预测玩家特征、未来行为和动机演变的大规模(数据驱动)应用程序。能够模拟玩家的动机并预测其演变的轨迹可能会导致个性化和动态的参与策略，从而能够根据玩家的特征和游戏中的行为进行调整。在工业和游戏化的背景下，实现类似的目标将是至关重要的。

Motivation can be loosely defined as a process of the brain and the mind, capable of driving and deeply shaping human behaviour. Motivational processes are embedded in many everyday life situations, exerting their effects via a wide range of incentive mechanisms and objects. Understanding this process in a videogame context, however, requires a more holistic approach considering not just the incentive properties of the game but also the player personal characteristics.My project aims to create reliable cross-games models of player motivation taking into account the contribution of natural inter individual variability. This will be accomplished linking in-game behavioural data and psychological models via a hybrid approach, where findings from small scale experimental studies (hypothesis-driven) will guide the realization of large scale (data-driven) applications for predicting players' characteristics, future behaviour and motivation evolution. Being able to model player motivation and predict the trajectories of its evolution could possibly lead to personalized and dynamic engagement strategies able to adapt accordingly to the player characteristics and in-game behaviour. Achieving a similar goal would be of pivotal importance in industrial and gamification contexts.