Seeing Migration Narratives: Enhancing Decision Making Through Visualisation of Policy Debates for Civil Society and the Media

移民和难民问题是英国和全球最复杂和最两极分化的政策挑战之一。人们认为，媒体关于移徙的报道对政策决定和公众对移徙的态度有重大影响。然而，关于移徙的媒体报道数量巨大，而且这些报道在数字平台上传播的复杂性极大，因此不可能利用现有工具跟踪和了解辩论中不同叙述、行为者和来源之间的关系。这为出现片面和误导性的公共辩论创造了空间，这些辩论可能被利用来产生不和谐和恐惧，并导致政策制定既不符合国家利益，也不符合移民和难民社区的利益。该项目将开发和应用自然语言处理，机器学习，统计和数据可视化的新技术：揭示关于移徙的数字话语的内容和性质;跟踪不同故事和概念的传播;展示辩论中不同声音的影响范围。这将为辩论中的权力和影响力的来源提供明确的证据，并使处理这一问题的民间社会行为者、决策者和记者能够就采取何种行动追究这一权力的责任作出知情的决定。

Migration and refugee issues are among the most complex and polarising policy challenges in the UK and globally. Media narratives on migration are perceived to have a significant impact on policy decisions and public attitudes toward migration. However the enormous number of media stories about migration, and the immense complexity of their diffusion around digital platforms make it impossible, using existing tools, to track and understand the relationship between different narratives, actors and sources in the debate. This creates space for the emergence of one-sided and misleading public debates, which can be exploited to generate discord and fear and lead to policy making that serves neither the national interest nor the interests of migrant and refugee communities.This project will develop and apply novel techniques from natural language processing, machine learning, statistics, and data visualisation to: reveal the content and nature of digital discourse on migration; track the diffusion of different stories and concepts; demonstrate the reach of different voices in the debate. This will provide clear evidence of the sources of power and influence within the debate, and allow civil society actors, policy makers and journalists dealing with the issue to make informed decisions on what action may be taken to hold this power to account.