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Presentation
Presentation
Visual and data journalism is experiencing an exponential growth in newsrooms of all types of media. The CU aims to provide students with the necessary tools to research, compile and analyse quantitative data, framing it in a journalistic narrative.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor | Semestral | 6
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Year | Nature | Language
Year | Nature | Language
3 | Mandatory | Português
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Code
Code
ULP451-2-22572
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
.1. Introduction to Data Journalism 1.1 History and evolution of data journalism 1.2 The 7 types of data stories 1.3 Examples: Público, The Pudding, Guardian, ProPublica 1.4 The "data mindset" - developing curiosity and skepticism 2. Data Fundamentals 2.1 Formulating journalistic hypotheses 2.2 Interviewing a database - first explorations 2.3 Data types and proxy fields 2.4 Ethics and data verification 3. Essential Technical Skills 3.1 Excel/Google Sheets for journalists 3.2 Data cleaning & basic analysis - sorting, filters, pivot tables 3.4 Applied basic statistics - means, medians, percentages, rate 4. Data Visualization 4.1 Design principles & tools - Flourish and Datawrapper 4.3 Accessibility and clarity 5. Narrative with Data 5.1 Transforming numbers into human stories 5.2 Narrative structure - from lead to data 5.3 Contextualizing statistics 5.4 Integrating multiple source 6. Advanced Tools (Intro) 6.1 Basic web scraping 6.2 Public APIs 6.3 R/Python overview (demo) 6.4 When Excel isn't enough
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Objectives
Objectives
Understand the fundamentals of data journalism, including the history of this practice. Search, compile and analyse data to tell stories in a journalistic editorial logic. Assess and verify the credibility of information sources. Mastery of basic concepts of statistics and quantitative methods. Basic programming skills for collecting, processing and presenting data in online jobs. Create interactive pieces according to the assumptions indicated by the reader (gender, age, geolocation, ...). Develop visual and storytelling strategies to illustrate social realities reflected in statistics, knowing how to integrate the conclusions of the data into the journalistic narrative. Master the use of analytics libraries and transparency tools for data journalism.
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Teaching methodologies and assessment
Teaching methodologies and assessment
Use of gamification as a method of peer evaluation of work produced in classroom context; learning through analysis and discussion of case studies; practical and progressive approach with bi-weekly assignments.
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References
References
Bounegru, L., & Gray, J. (2021). The Data Journalism Handbook: Towards a Critical Data Practice Amsterdam University Press. Cairo, A. (2013). The Functional Art - An Introduction To Information Graphics And Visualization. New Riders. Felle, T., Mair, J., Radcliffe, D., eds. (2015). Data Journalism: Inside the global future. Abramis Publishing. Garcia, R, Rosa, M. J., Barbosa, L. (2016). Que Número É Este? Um Guia Sobre Estatísticas Para Jornalistas. Fundação Francisco Manuel dos Santos. Gray, J., Chambers, L., & Bounegru, L. (2012). The data journalism handbook: How journalists can use data to improve the news. O'Reilly Media. Huff, D. (2013). Como Mentir com a Estatística. Gradiva. Miller, C. (2016). Getting Started with Data Journalism. Writing data stories in any size newsroom. Rogers, S. (2013). Facts Are Sacred. Faber & Faber. Usher, N. (2016). Interactive Journalism - Hackers, Data and Code. University of Illinois Press
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Office Hours
Office Hours
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Mobility
Mobility
No
