Understanding the Audience through Low-Level Interaction Data

Lead Research Organisation: University of Manchester
Department Name: Computer Science

Abstract

Collaboratively with the BBC the student is undertaking a series of investigative activities to understand how data around audience interaction with broadcast or online media can be used to measure enjoyment/engagement.
Activities include:
Investigating the literature to understand the types of data that may need to be collected and potential techniques with which it can be analysed and modelled;
Developing techniques for collecting data and designing experiments in which to apply these;
Collecting data in both small-scale lab experiments and at large-scale 'in the wild';
Applying data science/machine learning techniques to analyse data;
Developing and testing models of behaviour that indicate the extent to which an experience is successful.
The project enables the student to investigate research questions that will further understanding in both data science and interaction science. This research is centred on a 'real-world' problem, with access to the raw materials of data and industry experts at the BBC. The primary output of the studentship will be one or more models of how user engagement/behaviour manifests itself as interaction data.
The BBC gain understanding of the value of collecting different types of user data, and will be able to apply these models to audience data, thereby learning more about users and experiences.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/P510579/1 30/09/2016 29/09/2021
1943498 Studentship EP/P510579/1 31/08/2017 29/09/2021 Jonathan Carlton