11.4 Data Journalism and Digital Storytelling Techniques

Data journalism combines traditional reporting with data analysis to uncover hidden stories and provide evidence-based reporting. It uses tools for data collection, analysis, and visualization to explore complex issues and present findings in engaging formats.

Digital storytelling techniques like interactive graphics, immersive multimedia, and personalized data stories enhance the impact of data-driven journalism. These approaches have led to groundbreaking investigations, increased transparency, and informed public discourse on critical issues.

Data Journalism and Digital Storytelling

Definition of data journalism

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• Combines traditional journalism practices with data analysis and programming skills to uncover, analyze, and present stories
• Involves collecting, cleaning, and interpreting large datasets to find newsworthy insights and provide evidence-based reporting
• Enables journalists to uncover stories that might otherwise go unnoticed and hold power to account by revealing trends, patterns, and anomalies
• Increases credibility and impact of reporting by providing more in-depth and nuanced coverage of complex issues (climate change, healthcare)

Tools for data journalism

• Data collection and cleaning tools enable journalists to gather and process large datasets
  • Web scraping tools (Python libraries like BeautifulSoup and Scrapy) automate data collection from websites
  • Data cleaning tools (OpenRefine, Trifacta Wrangler) help standardize and correct errors in datasets
  • Knowledge of data formats (CSV, JSON, XML) is essential for working with various data sources
• Data analysis tools allow journalists to explore and derive insights from datasets
  • Spreadsheet software (Microsoft Excel, Google Sheets) is used for basic data analysis and manipulation
  • Statistical programming languages (R, Python) enable more advanced data analysis and modeling
  • SQL is used for querying and managing databases
• Data visualization tools help journalists present findings in engaging and accessible formats
  • Visualization libraries (D3.js, Matplotlib, ggplot2) allow for custom, interactive visualizations
  • Interactive visualization tools (Tableau, Flourish, Datawrapper) provide user-friendly interfaces for creating visualizations
• Programming skills are essential for data journalists to automate tasks and create custom tools
  • Proficiency in at least one programming language (Python, R, JavaScript) is necessary
  • Understanding of web development technologies (HTML, CSS) is important for creating online data stories
• Storytelling and communication skills are crucial for identifying newsworthy insights and presenting them effectively
  • Ability to identify compelling stories from data and provide context is key
  • Skills to present findings in a clear, engaging, and accessible manner are vital for impact

Digital storytelling techniques

• Interactive graphics allow users to explore data at their own pace and focus on areas of interest
  • Examples include interactive maps (election results), timelines (historical events), and charts (economic indicators) that respond to user input
• Data visualizations help convey complex information in a more accessible and engaging format
  • Infographics, heatmaps (crime rates), network diagrams (social connections), and 3D visualizations (anatomical models) make data more understandable
• Immersive multimedia combines various media elements to create a rich, engaging user experience
  • 360-degree videos (virtual tours), virtual reality experiences (simulations), and interactive documentaries (non-linear narratives) provide immersive storytelling
• Scrollytelling is a narrative technique that reveals content as the user scrolls down the page
  • Allows for a more linear, guided storytelling experience that unfolds gradually (step-by-step explanations, sequential reveals)
• Personalized data stories use data input by the user to create customized, relevant visualizations and narratives
  • Examples include tools that generate personalized recommendations (financial advice) or comparisons (carbon footprint) based on user-provided data

Impact of data-driven journalism

• ProPublica's "Dollars for Docs" (2010) revealed payments from pharmaceutical companies to doctors
  • Led to increased transparency and policy changes in the medical industry, such as mandatory disclosure of financial relationships
• The Guardian's "The Counted" (2015-2016) tracked killings by police in the United States
  • Contributed to the national conversation on police brutality and racial injustice, spurring protests and calls for reform
• The New York Times' "The Upshot" (ongoing) provides data-driven analysis of politics, policy, and everyday life
  • Helps readers understand complex issues (healthcare, education) and make informed decisions by presenting data in accessible formats
• The Washington Post's "Fatal Force" (ongoing) documents fatal shootings by police in the United States
  • Provides a comprehensive, up-to-date database for researchers, policymakers, and the public to analyze trends and patterns in police violence
• Reuters' "The Rohingya Exodus" (2017) used satellite imagery, data analysis, and eyewitness accounts to document the Rohingya refugee crisis
  • Drew international attention to the scale and severity of the humanitarian crisis, prompting calls for action and aid from governments and organizations