In the summer of last year ProPublica published a major investigation into air pollution in Florida, and its connection to the sugar industry. The story itself, Black Snow, is an inspiring example of scrollytelling — but equally instructive is the methodology article which accompanies it, responding to criticisms from the sugar industry.
Not only does it demonstrate how to respond when large organisations attack a piece of journalism — it also provides a great lesson on the tactics that are adopted by organisations when attacking data-driven stories.
In this post I want to break down the three most common attack tactics, how ProPublica deal with two of those, and how to use the same tactics during planning to ensure your project design isn’t flawed.
This week’s GEN Summit marked a breakthrough moment for artificial intelligence (AI) in the media industry. The topic dominated the agenda of the first two days of the conference, from Facebook’s Antoine Bordesopening keynote to voice AI, bots, monetisation and verification – and it dominated my timeline too.
At times it felt like being at a conference in the 1980s discussing how ‘computers’ could be used in the newsroom, or listening to people talking about the use of mobile phones for journalism in the noughties — in other words, it feels very much like early days. But important days nonetheless.
Ludovic Blecher‘s slide on the AI-related projects that received Google Digital News Initiative funding illustrated the problem best, with proposals counted in categories as specific as ‘personalisation’ and as vague as ‘hyperlocal’.
Women represent 49.5% of the world’s population, but they do not have a corresponding public, political and social influence. In recent years, more and more women have raised their voices, making society aware of their challenges — data journalists included. To commemorate International Women’s Day, Carla Pedret presentsa list of data journalism projects that detail the sacrifices, injustices and prejudices that women still have to face in the 21st century.
The list already boasts journalists from some of the leading data journalism projects in Latin America
A new data journalism mailing list for Spanish speakers has been launched by The National Institute for Computer-Assisted Reporting (NICAR) and its parent organisation, Investigative Reporters and Editors (IRE), reports Barbara Maseda.
NICAR-ESP-L, as it is called, seeks to be the Spanish version of NICAR-L, a mailing list in English that has been active for over 20 years. Continue reading →
Una nueva lista de correos en español dedicada al periodismo de datos ha sido puesta en marcha por el Instituto Nacional de Periodismo Asistido por Computadora (NICAR) y su organización madre, Reporteros y Editores de Investigación (IRE), radicada en la Universidad de Missouri, Estados Unidos.
NICAR-ESP-L es el nombre de este servicio que busca ser una versión en español de NICAR-L, una lista de correos en inglés que ya acumula más de 20 años de actividad.
Looking across the comments in the first discussion of the EJC’s data journalism MOOC it struck me that some pieces of work in the field come up again and again. I thought I’d pull those together quickly here and ask: is this the beginnings of a ‘canon’ in data journalism? And what should such a canon include? Stick with me past the first obvious examples…
Early data vis
These examples of early data visualisation are so well-known now that one book proposal I recently saw specified that it would not talk about them. I’m talking of course about… Continue reading →
Mass data gathering – scraping, FOI, deception and harm
The data journalism practice of ‘scraping’ – getting a computer to capture information from online sources – raises some ethical issues around deception and minimisation of harm. Some scrapers, for example, ‘pretend’ to be a particular web browser, or pace their scraping activity more slowly to avoid detection. But the deception is practised on another computer, not a human – so is it deception at all? And if the ‘victim’ is a computer, is there harm? Continue reading →
Journalists rely on two sources of competitive advantage: being able to work faster than others, and being able to get more information than others. For both of these reasons, I love scraping: it is both a great time-saver, and a great source of stories no one else has. Continue reading →