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’.
You may have seen a cute little Twitter hack — popularised by Andy Baio — which allows you to roll back the years and recreate a decade-old Twitter timeline. The twist is that you’ll be seeing updates from people who you may not have been following at the time but discovered later.
Nostalgia aside, the same technique could be used by journalists to track what was being said by any particular group of interest at a particular point in time. Here’s how. Continue reading →
Sometimes an organisation will publish a spreadsheet where only a part of the full data is shown when you select from a drop-down menu. In order to get all the data, you’d have to manually select each option, and then copy the results into a new spreadsheet.
It’s not great.
In this post, I’ll explain some tricks for finding out exactly where the full data is hidden, and how to extract it without getting Repetitive Strain Injury. Here goes…
To get the data from this spreadsheet you have to select 51 different options from a dropdown menu
One of the industry partners for the MA in Data Journalism is Haymarket Automotive (What Car?, PistonHeads and Autocar) — we’re now inviting applications from people who are particularly interested in studying data journalism in relation to the automotive sector. In other words, data motoring journalism!
You should have a passion for journalism and retail journeys, cars or the car industry, be interested in helping find new sources of data for stories, and working on stories based on data collected by third parties, and have lots of ideas that tap into the power of data-driven journalism.
Editorial director Jim Holder explains:
“The automotive industry is awash with historic data, from car specs to buyer behaviour, and populated by experts who believe they know how to produce and read it. But our brands – and buyer’s guide What Car? in particular – have unique access to live data from in-market car buyers. Harnessed properly, the data has the potential to surprise and delight the car industry, and car buyers – and shake-up outmoded suppositions and attitudes.”
Successful applicants approved by Haymarket will work with a Haymarket Automotive brand during part or all of their MA studies.
If you are interested, please apply through the course webpage specifying in your supporting statement that you are specifically interested in working with Haymarket Automotive.
Local data journalism in the UK has been undergoing a quiet revolution in the last 12 months, but 2018 in particular has seen a number of landmarks already in its first few months. Here’s some of the highlights in just its first 12 and a half weeks…
January: BBC Shared Data Unit publishes its first secondee-led investigation
The BBC Shared Data Unit had already been producing stories before in late 2017 it took on its first three-month secondees from the news industry. Over the next 12 weeks they received training in data journalism and work on a joint investigation. Continue reading →
The latest set of questions in the semi-regular FAQ section on this blog are about UGC, and come from a student at Liverpool John Moores. Here they are…
Is UGC more helpful or harmful to journalism?
Helpful, of course! Journalism has always relied on information and media (photos, video, audio) from readers/the audience and sources. The difference is that we now have access to a much larger amount of that information. Continue reading →
The deadline for the Data Journalism Awards is now just 3 weeks away. One category for educators and young journalists to look out for is the ‘Student and young data journalist of the year‘ which seeks to shine a light “the outstanding work of a new talent in data journalism, for projects done while they are still studying or early in their professional careers.”
The category is open to all data journalists under the age of 27 — but not students over that age (who I’m told should apply for the Best Individual Portfolio category). Submissions can include one or as many as ten pieces of data journalism. Winners get $1801 (the year William Playfair reportedly created the pie chart) and a trophy.