Predicting user state using machine learning

A non-transitory computer-readable storage medium storing computer program instructions executable by a processor of a system to perform steps for predicting user state comprising:

• obtaining a set of training data comprising service data for each service of a plurality of services coordinated by a network system for a plurality of users including a first user, wherein the service data obtained for a service includes activity data corresponding to a user's interactions with a user device when requesting the service, and an indication of a user state of the user at the time of requesting the service;
• training a computer model to predict the user state of the user using the obtained set of training data;
• receiving current user activity data corresponding to a set of features of a request for service from a first user device of the first user and user profile data corresponding to a set of features of past services requested by the first user;
• generating a plurality of user feature values for the first user, wherein each user feature value is determined based on a difference between an average of the values of a feature from the user profile data for the first user and the value of the feature from the current user activity data of the first user;
• generating a prediction of a state of the first user by providing the generated plurality of user feature values for the first user and a set of service features associated with the request for service from the first user as input to the trained computer model;
• and
• altering one or more parameters associated with a manner in which the network system coordinates a service for the first user based on the prediction about the state of the first user.