Computer-implemented system and method for determining attentiveness of user

A computer-implemented method of determining user attentiveness during media content consumption, the method comprising:

• obtaining, at a collection server, response data from a client device, wherein the response data is collected for a user consuming media content on the client device, and wherein the response data comprises a data stream representative of variation over time of the user's behaviour whilst consuming the media content;
• associating, at the collection server, the data stream with the media content;
• displaying, at a plurality of annotation devices, a dynamic representation of the response data;
• receiving, at the plurality of annotation devices, attentiveness data from an annotator, wherein the attentiveness data is an input score indicative of user attentiveness based on the dynamic representation;
• receiving, at an analysis server from the plurality of annotation devices, attentiveness data relating to the dynamic representation from a plurality of annotators;
• generating, by the analysis server, combined attentiveness data for the dynamic representation, the combined attentiveness data comprising an attentiveness parameter that is indicative of level of positive correlation between the attentiveness data from the plurality of annotators;
• associating, at the analysis server, the combined attentiveness data with events in the data stream or media content to generate attentiveness-labelled response data;
• storing, in a data repository, attentiveness-labelled response data from multiple users;
• extracting, from the data repository by the analysis server, an attentiveness-labelled response data training set;
• establishing, at the analysis server, an objective for a machine learning algorithm;
• and
• generating, using the machine learning algorithm, an attentiveness model from the attentiveness-labelled response data training set.

A system for determining user attentiveness during media content consumption, the system comprising:

• a collection server communicatively coupled via a network to a plurality of client devices, the collection server being configured to:
• obtain response data from the plurality of client devices, wherein the response data is collected for a user consuming media content on the client device, and wherein the response data comprises a data stream representative of variation over time of the user's behaviour whilst consuming the media content;
• and
• associate the data stream to the media content;
• an annotation device communicatively coupled to the collection server, the annotation device being configured to:
• display a dynamic representation of the response data concurrently with the media content to which it is associated;
• receive attentiveness data that comprises an input score indicative of user attentiveness based on the dynamic representation;
• and
• associate the attentiveness data with events in the data stream or media content to generate attentiveness-labelled response data;
• a data repository configured to store attentiveness-labelled response data from multiple users;
• and
• an analysis server communicatively coupled to the data repository, the analysis server being configured to:
• extract, from the data repository, an attentiveness-labelled response data training set;
• establish an objective for a machine learning algorithm;
• and
• generate, using the machine learning algorithm, an attentiveness model from the attentiveness-labelled response data training set.