Mass Communication and Journalism: Journalism Practice and News Writing Data Journalism Using data scraping visualisation

What It Is

Data journalism is the practice of using data analysis, visualization, and storytelling to communicate complex information to the public. A canonical example of data journalism is the "NYT's Snow Fall" project (2012), where The New York Times used interactive graphics, videos, and in-depth reporting to tell the story of a devastating avalanche in Washington state. This matters for media analysis because it highlights the potential of data journalism to engage audiences and convey nuanced information in a visually appealing way.

Key Terms & Concepts

• Data Journalism: The practice of using data analysis, visualization, and storytelling to communicate complex information to the public.
• Data Scraping: The process of extracting data from websites, databases, or other digital sources without permission.
• Data Visualization: The use of graphical and interactive elements to communicate complex data insights.
• Infographic: A visual representation of information that uses images, charts, and graphs to communicate data insights.
• Data Mining: The process of discovering patterns and relationships within large datasets.
• SQL: A programming language used to manage and analyze relational databases.
• API: An application programming interface that allows developers to access and manipulate data from external sources.
• Data Storytelling: The practice of using narrative techniques to communicate complex data insights in a compelling and engaging way.
• Data-Driven Journalism: The practice of using data analysis and visualization to inform and support journalistic reporting.
• Open Data: Publicly available data that is free to access and use.
• Data Journalism Tools: Software and platforms used to collect, analyze, and visualize data, such as Tableau, Power BI, and R.
• Data Journalism Ethics: The principles and guidelines that govern the use of data in journalism, including issues of data accuracy, transparency, and bias.
• Data Journalism Awards: Competitions that recognize excellence in data journalism, such as the Pulitzer Prize for Public Service.
• Data Journalism Education: Programs and courses that teach data journalism skills and principles, such as the Knight Center for Journalism in the Americas.

Common Misunderstandings

• Misunderstanding: Data scraping is illegal if it involves accessing private data without permission.
• Correction: Data scraping is legal if it involves accessing publicly available data, but it may still be subject to terms of service agreements and copyright laws. (Source: EFF v. AT&T, 2013)
• Misunderstanding: Data visualization is only for presenting complex data insights.
• Correction: Data visualization can be used to present a wide range of information, including simple statistics and trends. (Source: Tufte, 1983)
• Misunderstanding: Data mining is only for commercial purposes.
• Correction: Data mining can be used for a variety of purposes, including research, education, and journalism. (Source: Fayyad et al., 1996)

Quick Application / Identification

Scenario: A journalist wants to analyze the number of tweets about a particular topic over time. Which data journalism tool would be most suitable for this task?

Answer: Tableau. Explanation: Tableau is a data visualization tool that allows users to connect to external data sources, including social media APIs, and create interactive visualizations.

Scenario: A journalist wants to access data from a government website to analyze the impact of a policy change. What type of data is this an example of?

Answer: Open Data. Explanation: Open data is publicly available data that is free to access and use, which is the case with government websites that provide data in a machine-readable format.

Scenario: A journalist wants to create an infographic to present complex data insights to a general audience. What type of data visualization is most suitable for this task?

Answer: Infographic. Explanation: Infographics are visual representations of information that use images, charts, and graphs to communicate complex data insights in a visually appealing way.

Last‑Minute Revision

• Data journalism is a subset of investigative journalism. ⚠️
• The first data journalism award was the Pulitzer Prize for Public Service in 2012.
• Data mining is a type of data analysis that involves discovering patterns and relationships within large datasets.
• The Knight Center for Journalism in the Americas offers a data journalism course that covers the basics of data analysis and visualization.
• Data scraping is a type of data collection that involves extracting data from websites, databases, or other digital sources without permission.
• The EFF v. AT&T case (2013) established that data scraping is legal if it involves accessing publicly available data.
• Data visualization can be used to present a wide range of information, including simple statistics and trends.
• Tableau is a data visualization tool that allows users to connect to external data sources and create interactive visualizations.
• Open data is publicly available data that is free to access and use.
• Infographics are visual representations of information that use images, charts, and graphs to communicate complex data insights.
• Data journalism ethics are governed by principles such as data accuracy, transparency, and bias.
• The Pulitzer Prize for Public Service is a data journalism award that recognizes excellence in data journalism.
• Data journalism education programs teach data journalism skills and principles, such as data analysis and visualization.
• Data journalism tools include software and platforms used to collect, analyze, and visualize data, such as Tableau, Power BI, and R.