Data Journalism
데이터저널리즘
Introduction
Welcome to our Data Journalism course, an exciting and comprehensive journey designed to equip you with the skills necessary to become a proficient data journalist. Over 15 weeks, you will learn about the fundamentals of journalism and data-driven storytelling, master data manipulation and visualization techniques using R and Tableau, and delve into ethical and legal considerations.
Throughout the course, you’ll develop a strong foundation in identifying newsworthy stories, conducting interviews, and fact-checking information. You will also gain hands-on experience in data cleaning, preprocessing, exploratory analysis, and various data visualization techniques, including advanced chart types and interactivity.
By the end of this course, you will have completed a data journalism project incorporating data analysis, visualization, and journalistic storytelling. With a solid understanding of the concepts and tools covered, you’ll be well-prepared to apply your skills in the ever-evolving field of data journalism.
Syllabus
Week 1: Introduction to Journalism and Data Journalism
What is Journalism?
Fundamentals of news writing and reporting
The importance of data-driven storytelling
What is Data Journalism?
Overview of tools: R, Tableau, and others
Week 2: Finding and Evaluating News Stories
Identifying newsworthy stories
Generating story ideas
Evaluating story angles and potential impact
Sourcing data for stories
Evaluating data quality and credibility
Week 3: Interviewing and Fact-Checking
Principles of journalistic interviewing
Preparing for and conducting interviews
Fact-checking and verifying information
Ethical considerations in interviewing and reporting
Week 4: Data Cleaning and Preprocessing
Introduction to data manipulation in R (tidyverse)
Data cleaning, filtering, and aggregation
Data transformation and handling missing data
Data normalization and scaling
Week 5: Descriptive Statistics and Exploration
Descriptive statistics in R
Exploratory data analysis (EDA) with R
Identifying trends, patterns, and outliers
Asking the right questions
Week 6: Introduction to Data Visualization with R
Introduction to ggplot2
Grammar of graphics with ggplot2
Customizing plots: themes, scales, labels, and titles
Different types of plots and when to use them
Week 7: Advanced Data Visualization with R
Advanced ggplot2 techniques
Faceting and multi-panel plots
Time series and geospatial data visualization
Interactive visualizations with plotly or ggplotly
Week 8: Introduction to Tableau
Tableau interface and basics
Connecting Tableau to data sources
Creating and customizing visualizations in Tableau
Week 9: Advanced Data Visualization with Tableau
Advanced chart types and techniques in Tableau
Creating dashboards and stories in Tableau
Interactive and dynamic visualizations in Tableau
Geospatial data visualization in Tableau
Week 10: Combining R and Tableau
Exporting R data and visualizations to Tableau
Integrating R scripts within Tableau
Leveraging the strengths of both tools for data journalism
Week 11: Crafting Compelling News Stories
Structuring news articles and data-driven stories
Balancing text and visualizations
Writing clear and concise news copy
Incorporating quotes and interview material
Ensuring accuracy and transparency
Week 12: Digital Writing and Interactive Media with Shiny and Quarto
Introduction to Shiny and Quarto for interactive media
Creating Shiny apps and Quarto websites for digital storytelling
Embedding data visualizations and interactive elements
Best practices for designing engaging and accessible digital content
Week 13: Legal and Ethical Considerations
Data privacy and security
Copyright and licensing issues
Responsible data reporting and fact-checking
Avoiding bias and promoting inclusivity in journalism
Week 14: Team project consultation
Week 15: Project presentation
Students present their data journalism projects
Projects should incorporate data analysis, visualization, and journalistic storytelling
Feedback and discussion on projects
Reflecting on the course and potential future applications in the field of data journalism