Understanding the Audience through Low-Level Interaction Data

与英国广播公司合作，该学生正在开展一系列调查活动，以了解如何使用有关观众与广播或在线媒体互动的数据来衡量乐趣/参与度。活动包括：调查文献，了解可能需要收集的数据类型和分析和建模的潜在技术；开发收集数据和设计实验的技术，并在其中应用这些技术；在小规模的实验室实验和大规模的野外实验中收集数据；应用数据科学/机器学习技术分析数据；开发和测试行为模型，以表明经验成功的程度。该项目使学生能够调查研究问题，这将进一步理解数据科学和交互科学。这项研究以一个“现实世界”的问题为中心，可以接触到BBC的原始数据和行业专家。学生的主要产出将是一个或多个用户参与/行为如何表现为交互数据的模型。BBC了解到收集不同类型用户数据的价值，并将能够将这些模型应用于受众数据，从而更多地了解用户和体验。

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.