O Jornalismo Guiado por Dados é uma prática de Jornalismo em Bases de Dados em vias de adoção por redações de todo o mundo, desde meados dos anos 2000. Trata-se de um desenvolvimento dos conceitos de Jornalismo de Precisão e Reportagem... more
O Jornalismo Guiado por Dados é uma prática de Jornalismo em Bases de Dados em vias de adoção por redações de todo o mundo, desde meados dos anos 2000. Trata-se de um desenvolvimento dos conceitos de Jornalismo de Precisão e Reportagem Assistida por Computador, propostos inicialmente nos anos 1970 e impulsionados pelo processo de digitalização das redações e pela adoção de políticas de acesso à informação por governos e instituições. O trabalho levanta a hipótese de que o Jornalismo Guiado por Dados se configura como uma imbricação entre a cultura profissional dos jornalistas e a cultura hacker. Os resultados da etapa preliminar de uma pesquisa etnográfica realizada entre jornalistas brasileiros em novembro e dezembro de 2012 sugerem que os jornalistas guiados por dados compartilham algumas práticas e valores com os membros da cultura hacker.
Data Driven Journalism is a practice in the process of adoption by newsrooms around the world since the mid 2000s. It is a development of the concepts of Precision Journalism and Computer-Assisted Reporting, initially proposed in 1970, which has gained momentum by the digitization process of newsrooms and the adoption of policies on access to information by governments and institutions. The paper hypothesizes that Data Driven Journalism is configured as an overlap between the professional culture of journalists and hacker culture. The results of the preliminary stage of an ethnographic study of Brazilian journalists, carried forward in November and December of 2012, suggest that data-driven journalists do share some common practices and values with the members of hacker culture.
As quantitative forms have become more prevalent in professional journalism, it has become increasingly important to distinguish between them and examine their roles in contemporary journalistic practice. This study defines and compares... more
As quantitative forms have become more prevalent in professional journalism, it has become increasingly important to distinguish between them and examine their roles in contemporary journalistic practice. This study defines and compares three quantitative forms of journalism—computer-assisted reporting, data journalism, and computational journalism—examining the points of overlap and divergence among their journalistic values and practices. After setting the three forms against the cultural backdrop of the convergence between the open-source movement and professional journalistic norms, the study introduces a four-part typology to evaluate their epistemological and professional dimensions. In it, the three forms are classified according to their orientation toward professional expertise or networked participation, transparency or opacity, big data or targeted sampling, and a vision of an active or passive public. These three quantitative journalistic forms are ultimately characterized as related but distinct approaches to integrating the values of open-source culture and social science with those of professional journalism, each with its own flaws but also its own distinct contribution to democratically robust journalistic practice.
Despite claims of continuity, contemporary data journalism is quite different from the earlier tradition of computer-assisted reporting. Although it echoes earlier claims about being scientific and democratic, these qualities are understood as resulting from better data access rather than as being something achieved by the journalist. In the context of Big Data in particular, human subjectivity tends to be downgraded in importance, even understood as getting in the way if it means hubristically theorising about causation rather than working with correlation and allowing the data to speak. Increasing ‘datafication’ is not what is driving changes in the profession, however. Rather, the impact of Big Data tends to be understood in ways that are consonant with pre-existing expectations, which are shaped by the broader contemporary post-humanist political context. The same is true in academic analysis, where actor–network theory seems to be emerging as the dominant paradigm for understanding data journalism, but in largely uncritical ways.
This is the proof of my introductory chapter to News, Numbers and Public Opinion in a Data-Driven World, which I edited and published through Bloomsbury Academic (2018). There might be differences between this and the published version.
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... more
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 of identifying and telling stories. What we observe as a result is the emergence of a new journalistic sub-field often described as ‘computational/data journalism’. This study focuses on the output of data journalism; by using a classic 'handmade' standardised content analysis methodology it aims to contribute to a better understanding of its reporting styles. 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 – from 2013 to 2015 (n= 179). Our categories of analysis look at, amongst other aspects, data sources and types, visualisation strategies, interactive features, topics, and types of media outlets nominated. Results show that over 40 percent of the data-driven pieces were published on the websites of (daily or weekly) newspapers and nearly 20 percent came from non-profit organisations for investigative journalism like ProPublica. Almost half of the cases cover a political topic, and social, economic as well as health and science 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 an official source like Eurostat. Further analyses regard the differences between 2013, 2014 and 2015 and look deeper into visualisation strategies and interactive features.
Computer-assisted news reporting refers to anything that uses computers to aid in the newsgathering process. The introduction of computers in the newsroom has been a gradually developing process that must be traced back to early... more
Computer-assisted news reporting refers to anything that uses computers to aid in the
newsgathering process. The introduction of computers in the newsroom has been a gradually
developing process that must be traced back to early computing devices. Later advances
included inventions by John Napier, Blaise Pascal, and Charles Babbage. A breakthrough in
computing was the invention of Herman Hollerith's Tabulator and Sorter. Soon after, Howard
Aiken developed the Mark I computer. By the 1950s, the computing revolution had begun. The
first actual instance of computer assisting reporting was with the 1952 presidential election
when CBS employed the Remington Rand UNIVAC to predict the outcome of the race between
Eisenhower and Stevenson. A decade later several pioneers such as Philip Meyer and Elliot
Jaspin began to successfully initiate new computing techniques for reporting. Computer-
assisted news reports by Clarence Jones, David Burnham, Don Barlett, and James Steele soon
followed. By the 1980s microcomputers became commonplace and their introduction into
newsrooms occurred in several stages: first, individual reporters bought their own computers;
later, organizations purchased them; initially microcomputers were primarily used for word
processing but one of the newer purposes was to connect to online databases. Computer-
assisted reporting has recently found great success in newsrooms across the country, but it only
came about because of the initiative of a few pioneers. For computer-assisted journalism to
become so successful, it was necessary for basic reporting skills to already be in place.
When an earthquake occurred at 6:25 a.m. on March 17, it may have given “robot” journalism its first big break. The early morning tremblor allowed an algorithm created by L.A. Times programmer and journalist Ken Schwencke to report the... more
When an earthquake occurred at 6:25 a.m. on March 17, it may have given “robot” journalism its first big break. The early morning tremblor allowed an algorithm created by L.A. Times programmer and journalist Ken Schwencke to report the story ahead of other outlets. The story took only about three minutes to appear online, drawing information such as the quake’s time, magnitude and epicenter from the United States Geological Survey and inserting it into a prefabricated template.
This came some 40 years after the first story-writing algorithm was created at Yale University in 1977. Now, the Associated Press says it will distribute financial reports generated by Automated Insights software. These stories will draw from information produced by an investment research company. AP, which has acquired a small stake in Automated Insights, expects the new method will allow it to publish 10 times as many earnings reports as in the past.
AP Managing Editor Lou Ferrara says rather than replace human reporters, automation will free them up for more meaningful work, such as identifying trends and locating exclusives. Algorithmic copy has been seeping into newspapers for a few years now. Ferrara said AP had already used the technology to generate sports stories from box scores. Other boilerplate news may follow.
