本科生课程、英文课程
课程简介
大数据时代为科学家、社会学家以及政策法规制定者带来了理解自然和人类社会的新机遇。然而，数据科学的从业者往往面临着将数据洞察转化为具有说服力的阐释的挑战，比如，网络内容产品、新闻报道、科普内容、政策说明等。数据叙事有哪些基本要素？如何用大数据辅助叙事语言？何种工具和方法可以用于高效的数据叙事？数据辅助下的叙事有哪些优秀的实践经验？
海量数据并不一定带来具有洞见和说服力的叙事。大数据的描述、分析、可视化与呈现往往缺乏经过仔细设计的叙事框架。本课程将关注大数据与叙事之间的相互联系，帮助高年级本科生得以使用大数据构建有信息量、行之有效、有说服力的叙事框架。学生将从本课程中学习必要的方法、技能、经验以辅助数据驱动的内容产品设计，新闻作品创作，科学传播报告和社会研究。
本课程欢迎尚未接触过数据科学的同学选修，同时，希望对数据分析尚且陌生的同学在学习本课程的过程中开始尝试使用数据叙事的不同工具或程序语言。同时，已掌握数据分析与可视化方法的同学通过本课程将会提高其数据叙事的技巧与策略。
The era of big data has created exciting new opportunities for scientists, social scientists, and policymakers to explore and understand nature and society. However, practitioners in data science often encounter difficulties in translating data-driven insights into powerful narratives in web content products, news reports, science briefs, or policy guidelines. What are the fundamental elements of successful data storytelling? How to use big data to assist social science and humanities storytelling? Which toolkits and techniques could be used to produce compelling data storytelling? What are the best practices of data-assisted storytelling in different fields?
A large amount of data does not necessarily bring insightful and persuasive storytelling. A well-designed narrative framework is often missing in the descriptions, analytics, visualisation, and presentation of big data. This course will focus on the intersection of big data and storytelling, aiming to enable undergraduate students to produce informative, effective, and compiling narrative frameworks using big data. Students will learn essential skills, techniques, and experiences to produce successful data-driven content products, journalistic reports, science communication articles, and social sciences research.
The course welcomes students who are new to data science, but we strongly encourage students who do not yet have experience with data analytics to start exploring different software and coding languages for data storytelling during the course. Meanwhile, students familiar with data analytics and visualisations will also learn how to improve their techniques and strategies for completing data storytelling.
教学目标
1、了解数据叙事的基本原则、成功案例
2、基本掌握数据叙事主要工具和方法
3. 掌握如何将数据叙事变得更具活力的技巧
4、有能力创作出数据叙事在不同应用场景下的作品，比如，数据驱动的互联网内容产品设计、科学报道、数据新闻、文化分析与社会研究等。
The course will focus on basic guidelines, powerful toolkits and strategies, best practices and implications of data storytelling. We will start from an introduction of foundations in data storytelling and useful toolkits for effective data narratives in the first half of the term. In the second half of the term, we will explore dynamic perspectives to data storytelling as well as good practices of using data to create persuasive narratives in different fields, for example, internet content designs, science reporting, data journalism, cultural analytics and social science research.
考核方式
课程教学将以每周两小时的讲课为主，同时伴有每周的课堂结束后的讨论与学生展示。课堂签到与参与占总成绩权重20%。作为一门非常注重实践技能的课程，选课同学将通过课程期末论文进行考核。期末论文可以提交数据叙事的文章、音频或视频成果，针对数据叙事所有应用领域中其中一个领域。课题需要遵循数据叙事的基本原则并且尽可能使用多元的叙事结构和框架。期末成绩占成绩权重80%。
There will be weekly lectures, followed by seminars of discussions and student-led presentations. Presentation and discussion in the course account for 20% of overall scores. As a highly practical course, students will also be assessed through a final project submitted by the end of the term. The project will provide a data storytelling article/audio/video for one of the data narratives fields. The project should follow the fundamentals of data narratives and use dynamic perspectives to produce the narrative where possible. The final project will account for 80% of overall scores.