Artificial intelligence for journalism is both promising and overhyped. Computational journalist Jonathan Stray dug into the state of AI in investigative reporting, outlining for GIJN where the near-future opportunities lie.
What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from April 8 to 14 finds a zine focused on machine learning-powered investigative journalism produced by @bxrobertz, a video explainer from @FT on whether big corporations are really generous or just avoiding taxes, @knowtheory and @amandabee reviewing seven optical character recognition tools and @workbenchdata offering a tutorial on visualizing @Twitter data.
There are two ways to use machine learning in journalism: as part of investigative reporting, or as a day-to-day tool to make journalists’ lives easier. But the journalism industry is still scratching the surface when it comes to machine learning and deep learning.
With the global spread of data journalism, the advent of artificial intelligence and the increasing use of big data moving alongside a rapid rise of disinformation, GIJN asked data journalism experts around the world what they anticipate for 2019. Here are their thoughts on the major trends, ideas and technologies that will affect how we do our jobs.
What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from December 31, 2018 to Jan 6, 2019 finds experts sharing their thoughts on machine learning in journalism with @storybench, @funkeinterativ and @webk1d’s useful tool to merge datasets, @pewresearch’s overview of female under-representation in online image searches, and an analysis by @EDNNews on corpses bodies sent back to El Salvador.
What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from Aug 20 to 26 finds @Numerama analyzing the representation of women in @netflix series and finds it lacking, @AJEnglish creating an interactive explainer on how 2 million Muslims make the pilgrimage to Mecca every year, @FT readers brainstorming air pollution solutions for London, and @Bastamag digging into data of @Airbnb — a cash cow for home renters.
What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from June 4 to 10 finds an awesome curated list of resources for visualizing music by @Willian_justen, a deep dive into unsolved murders across America by @washingtonpost and @CarbonBrief mapping of the past, present and future of global coal power plants.
Using image analysis tools on their own means nothing without asking the right questions. AJ Labs experimented with Google Vision API, a machine-learning technology, to analyze images used by Al Jazeera over the course of last year. They hope to integrate the technology into their newsroom in the future to make processes easier for their journalists.
What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from Sept 11 to 17 has @puntofisso using machine learning to map the average face of British politicians, @AftertheFloodco creating a font that turns numbers into sparklines, and @datassist listing seven deadly sins in statistical analysis.
