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Class Data Journalism and Digital Methods

  • Presentation

    Presentation

    In a scenario where digital information is multiplying all the time, data plays a transformative role in the production and dissemination of news. For the contemporary journalist, mastering the access, extraction, analysis and interpretation of data is fundamental to generating accurate, contextualized and evidence-based reports. Similarly, communicating the results clearly and effectively requires mastery of the most appropriate digital design and visualization techniques, capable of translating the complexity of data into intuitive, easy-to-understand information.   This course aims to provide integrated training - combining theory and practice - in the fields of data analysis, information visualization and digital design. In addition, Digital Methods are incorporated into the subject, covering not only the use of specialized programs for the study and analysis of platforms and social media, but also the journalistic potential of these platforms for professionals in the field.  
  • Code

    Code

    ULHT7158-27479
  • Syllabus

    Syllabus

    Data types, formats, and tools. Data analysis and processing. Visual narratives and data exploration. Design and visual coding. Fundamentals of Digital Methods. Social network analysis tools. Fundamentals of the Interconnected Journalism.
  • Objectives

    Objectives

    This course unit is designed to provide theoretical and practical training in data journalism, digital methods and connected journalism, equipping students with the knowledge, skills and competences required to work in these fields. The programme prepares students to develop, plan and manage empathetic projects involving data analysis and interpretation, transforming information into journalistic narratives supported by interactive visualisations. By the end of the course module, students should be able to: Handle, interpret and analyse data; Explore data from social media; Use data analysis and visualisation tools; Apply principles of information and interaction design; Code, structure and organise information; Plan and develop an Interconnected feature; Understand and utilise the affordances of the main social media platforms in the production and distribution of journalistic content.
  • Teaching methodologies

    Teaching methodologies

    The UC adopts an approach that combines active methodologies to provide a robust theoretical and practical education. With the implementation of the flipped classroom, students have prior access to the course content, reserving face-to-face time for the analysis of case studies, problem-based learning and project development. This practice fosters autonomy, critical thinking and informed decision-making.   Project-based learning encourages students to tackle complex challenges and propose innovative solutions, using digital tools for data analysis and visualisation. Finally, the emphasis on adapting to new patterns of information consumption enables students to transform data into valuable insights and clear, engaging journalistic content, preparing them to work independently and creatively in the labour market.  
  • References

    References

    Bradshaw, P. (2021). Finding Stories with Spreadsheets. Leanpub. Cardoso, C. R., & Figueiras, A. (2024). Editorial | The Inspiring Role of Magazine Studies: The Interconnected Journalism Example. International Journal of Magazine Studies, 1(1), 4-9. Houston, B. (2018). Data for journalists: a practical guide for computer-assisted reporting. Routledge. Kirk, A. (2019). Data visualisation: A handbook for data driven design. SAGE Publications Ltd. Norman Donald, A. (2013). The design of everyday things. MIT Press. Quan-Haase, A., & Sloan, L. (Eds.). (2022). The SAGE handbook of social media research methods. SAGE Publications Ltd. Rogers, R. (2024). Doing digital methods. SAGE Publications Ltd. Segel, E., & Heer, J. (2010). Narrative visualization: Telling stories with data. IEEE transactions on visualization and computer graphics, 16(6), 1139-1148. Tufte, E. (2001). The Visual Display of Quantitative Information. Graphics Pr.  
  • Assessment

    Assessment

    Descrição

    Ponderação

    Assiduidade/Participação nas aulas

    20%

    Trabalho em Grupo

    30%

    Projeto individual

    50%

     

     

     

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