Related Papers
Journalism Education
Visualising data stories together: Reflections on data journalism educationfrom the Bournemouth University Datalabs Project
2016 •
Özlem Demirkol
Ana Serrano Tellería
In very few years in journalism, we have gone from looking at social science techniques, what was called precision journalism, to dealing with open data as a huge source of information that lead us to data journalism what connects with data science in the sense of using -again- scientific methods to extract knowledge and insights from structured data. This article offers an overview of that evolution and focuses on some prototypes that have emerged in this new journalistic ecosystem of data journalism, data visualization and data literacy.
DATA AND TECHNOLOGY: ONE OF THE CHALLENGES FOR JOURNALISM (Atena Editora)
DATA AND TECHNOLOGY: ONE OF THE CHALLENGES FOR JOURNALISM (Atena Editora)
2022 •
Atena Editora
In the constantly changing society we live in, the way journalism is done has undergone major changes. However, it must be noted that the pillars of journalism continue to be based on ethical values, the search for truth and objectivity. One of the factors contributing to change in this profession is the widespread use of new technologies. In this work, in order to adjust teaching to the new emerging needs of future professionals, we will focus on the information contained in the data and how to analyze it, since the data have been increasingly used as a source of news. The proposed challenge was to analyze how three leading Portuguese newspapers covered the news of the pandemic caused by COVID-19. In this sense, it was necessary to prepare the database for analysis and plan what information to extract from the data. In addition to Excel, used to organize the database, we used the Python programming language, which allowed for a more detailed analysis of the news coverage of the pandemic.
JOU 353 Big Data Small Screens The Art and Science of Responsive Data Journalism
Carl V . Lewis
● On-Demand Office Hours Reservations: http://bit.ly/dataj-office-hours I. Rationale Unlike any time before in our lives, we have access to vast amounts of free information––a phenomena scholars refer to as " big data. " With the right tools, we can start to make sense of all this data to see patterns and trends that would otherwise be invisible to us. By transforming numbers into graphical shapes and interactive web apps, we can allow users to understand the stories those numbers hide. This process of gaining new insights from data and crafting visual stories to convey that data in an accessible and engaging format is part of what we call " data journalism " –– a specialty subset of journalism that reflects the increased role that numerical data is used in the production and distribution of information in the digital era.
Digital Journalism
Waiting for Data Journalism
2014 •
Manon Libert
When data become news. A content analysis of data journalism pieces.
Wiebke Loosen, Julius Reimer, Fenja De Silva-Schmidt
Conference Paper for the Future of Journalism conference 2015: Risks, Threats and Opportunities, September 10-11th 2015, Cardiff University, UK. Abstract: For journalism the phenomena of ‘big data’ and an increasingly data-driven society are doubly relevant: First, it is a topic worth covering so that the related developments and their consequences are made understandable and debatable for the public. Second, the ‘computational turn’ has already begun to affect practices of news production and is giving rise to novel ways to identify and tell stories. Thus, what we observe is the emergence of a new journalistic sub-field mostly described as ‘computational/data journalism’. This study focuses on the output of data journalism – with the aim of contributing to a better understanding of its reporting styles. The method used is a classical ‘handmade’ standardised content analysis. The sample consists of all the pieces that were nominated for the Data Journalism Award (DJA) – an award issued annually by the Global Editors Network – in 2013 and 2014 (n= 120). Categories of analysis look at, amongst other aspects, data sources and types, visualisation strategies, interactive features, topics, and types of nominated media outlets. Results show that over 40 percent of the data-driven pieces were published on the websites of (daily or weekly) newspapers; just over 20 Percent came mainly from non-profit organisations for investigative journalism like ProPublica. Almost half of the cases cover a political topic, and social and scientific issues appear frequently too. Financial data and geodata are the types of data used most often and most of the data relates to a national context. More than two-thirds of the projects use data from official sources like Eurostat. Further analyses regard differences between 2013 and 2014 and look deeper into visualisation strategies and interactive features.
Studies in Media and Communication
The Principles, Features and Techniques of Data Journalism
2018 •
Andreas Veglis
Digital and computational technology is steadily developing and continually bringing changes in the field of journalism, which faces a major crisis, as people's trust in the media continues to decrease. This paper studies the subject of data journalism which is increasing in popularity and is considered to be at the forefront of these changes. This kind of journalism may be a way to re-establish and strengthen journalism's value, as well as to reassure its sustainability. Datasets, tools, policies on Freedom of Information and transparency and professionals become constantly available for data journalism to flourish. However, there are still many challenges along with skepticism and confusion around its role and value in the field. In the near future, data journalism seems to gain more trust by the news organization and the public, as both start to comprehend its potentials.
Asia Pacific Media Educator
Data Journalism Teaching, Fast and Slow
2018 •
Paul Bradshaw
The Field Guide to Data Science
Bob Sagget
TOWARDS A TAXONOMY OF DATA JOURNALISM
Andreas Veglis
In recent years data journalism has drawn significant attention not only in academic literature but also in the media sector. Data Journalism is a new form of journalism that has gradually appeared over the last decade, driven by the availability of data in digital form. Currently a significant amount of data journalism projects are being produced all over the world. These projects vary considerably in terms of structure and visualization characteristics. As a result of the above it would be interesting to propose a taxonomy of data journalism projects that can help future data journalists to choose the appropriate type of projects that will be suitable for their needs. This classification could be based on certain characteristics of the data journalism projects. The proposed taxonomy will take into account various parameters that play an important role in data journalist projects and especially in the type and the role of the visualization.
