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想的一个过程，能够驱动和深刻地塑造人类的行为。动机过程嵌入在许多日常生活情境中，通过广泛的激励机制和客体发挥其作用。然而，在电子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玩家动机跨游戏模型，同时考虑到自然个体间可变性的贡献。这将通过混合方法将游戏行为数据和心理模型联系起来，其中小规模实验研究（假设驱动）的发现将指导大规模（数据驱动）应用的实现，以预测玩家的特征、未来行为和动机演变。如果能够模拟玩家动机并预测其演变轨迹，便有可能创造出能够适应玩家特征和游戏内行为的个性化动态粘性策略。在工业和游戏化环境中，实现类似的目标至关重要。

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.