Understanding the Audience through Low-Level Interaction Data

这名学生与英国广播公司合作，开展了一系列调查活动，以了解观众与广播或在线媒体互动的数据如何被用来衡量享受/参与程度。活动包括：调查文献，以了解可能需要收集的数据类型，以及可以用来分析和建模的潜在技术；开发收集数据的技术并设计应用这些数据的实验；在小规模实验室实验和大规模“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，表明经验的成功程度。该项目使学生能够调查研究问题，这将加深对数据科学和交互科学的理解。这项研究的核心是一个“现实世界”的问题，即英国广播公司可以获得数据的原材料和行业专家。学员资格的主要输出将是一个或多个用户参与/行为如何表现为互动数据的模型。BBC了解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，从而了解更多关于用户和体验的信息。

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.