Automated prediction of user response states based on traversal behavior
AssigneeZynga Inc.
InventorsLuke Dicken, Johnathan Pagnutti, Yang Wen
Life of this patent
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Abstract
A game management system is configured for automated analysis of player behavior regarding traversal of different screens and options in a game application (as opposed to exclusively gameplay behavior) and to generate an automated estimation or inference about one or more psychological aspects of player behavior, such as motivation for game engagement and/or emotional states at different stages of interaction. The results of such analysis are automatically parametrized and included in a multidimensional parametric player model that informs player clustering and/or automated customization of game content.
Claims20
A method comprising:
- receiving behavior data for multiple players of a computer-implemented game, the behavior data indicating interaction journeys by respective players within the game, each interaction journey comprising a sequence of actions selected from a predefined set of actions;
- based on the behavior data, compiling behavior graph data in which interaction journeys are represented as respective directed graph structures in which each action in the corresponding sequence of actions is represented as a respective action node;
- storing the behavior graph data in a graph database,
- accessing label data that indicates assigned associations between a plurality of psychological labels and the behavior graph data, each psychological label pertaining to a respective psychological feature of player experience or player behavior;
- using the behavior graph data and the associated label data, training an artificial neural network for automated label prediction, thereby providing a trained neural network;
- and
- using the trained neural network, producing a psychological label prediction for a player based on a particular interaction journey by the player.
A system comprising:
- one or more computer processor devices;
- and
- memory storing instructions to configure the system, when the instructions are executed by the one or more computer processor devices, to perform operations comprising:
- receiving behavior data for multiple players of a computer-implemented game, the behavior data indicating interaction journeys by respective players within the game, each interaction journey comprising a sequence of actions selected from a predefined set of actions;
- based on the behavior data, compiling behavior graph data in which interaction journeys are represented as respective directed graph structures in which each action in the corresponding sequence of actions is represented as a respective action node;
- storing the behavior graph data in a graph database;
- accessing label data that indicates assigned associations between a plurality of psychological labels and the behavior graph data, each psychological label pertaining to a respective psychological feature of player experience or player behavior;
- using the behavior graph data and the associated label data, training an artificial neural network for automated label prediction, thereby providing a trained neural network;
- and
- using the trained neural network, producing a psychological label prediction for a player based on a particular interaction journey by the player.
A non-transitory computer-readable storage medium having stored thereon instructions that, when executed by one or more computer processor devices, cause the one or more computer processor devices to perform operations comprising:
- receiving behavior data for multiple players of a computer-implemented game, the behavior data indicating interaction journeys by respective players within the game, each interaction journey comprising a sequence of actions selected from a predefined set of actions;
- based on the behavior data, compiling behavior graph data in which interaction journeys are represented as respective directed graph structures in which each action in the corresponding sequence of actions is represented as a respective action node;
- storing the behavior graph data in a graph database;
- accessing label data that indicates assigned associations between a plurality of psychological labels and the behavior graph data, each psychological label pertaining to a respective psychological feature of player experience or player behavior;
- using the behavior graph data and the associated label data, training an artificial neural network for automated label prediction, thereby providing a trained neural network, and
- using the trained neural network, producing a psychological label prediction for a player based on a particular interaction journey by the player.
Dependencies are inferred from the claim text.