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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 State of the Art 1.1 Evolution and specialization – from “Computer-assisted reporting” to “Journo-coders” 1.2 Interactivity and data - benchmark cases 1.3 “Precision journalism” and the importance of formulating a hypothesis in data journalism 2. Interviewing a database 2.1 Numbers as a way of telling journalistic narratives 2.2 Interactivity in dynamic media – the power of hyperpersonalization 2.3 News and statistics values ¿¿– a conflict or an ally? 2.4 Building an hypothesis and design a methodology 2.5 Statistical concepts 2.6 From data to formats – from inverted pyramid to funnel narrative 2.7 Types of data and search for sources; data checking 3. Data analysis 3.1 Data cleaning and analysis 3.2 Analysis in a spreadsheet, R programming language, web scraping, extracting data from pdf 4. Visual storytelling 4.1. International and national benchmark 4.2. Visual strategies for data stories 4.3. Data visualization: literacy, production tools, web development and machine learning
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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
Gamification will be used as a method of heteroevaluating work produced in a classroom context; learning through analysis and discussion of case studies
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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
