Here’s a quick experiment in data visualisation to provide an instant insight into a story on how the blame game is being played by columnists. The data is taken from a Liberal Conspiracy blog post – I’ve transferred that into a spreadsheet with limited categories and used the Gauges gadget to visualise the totals. A screengrab is below – but
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Mauro Accurso has followed up his rapid translation of last week’s inverted pyramid of data journalism with a Spanish version of part 2: the 6 C’s of communicating data journalism. It’s copied in full below. La semana pasada les traduje la primera parte de La Pirámide Invertida del Periodismo de Datos de Paul Bradshaw que prometió extender en el aspecto de
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Last week I published an inverted pyramid of data journalism which attempted to map processes from initial compilation of data through cleaning, contextualising, and combining that. The final stage – communication – needed a post of its own, so here it is. UPDATE: Now in Spanish too. Below is a diagram illustrating 6 different types of communication in data journalism.
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To corrupt a well known saying, “cook a man a meal and he’ll eat it; teach a man a recipe, and maybe he’ll cook for you…”, I thought it was probably about time I posted the recipe I’ve been using for laying out Twitter friends networks using Gephi, not least because I’ve been generating quite [...]![]()
Last summer, at the European Centre for Journalism round table on data driven journalism, I remember saying something along the lines of “your eyes can often do the stats for you”, the implication being that our perceptual apparatus is good at pattern detection, and can often see things in the data that most of us [...]![]()
A post on the Guardian Datablog earlier today took a dataset collected by the Tweetminster folk and graphed the sorts of thing that journalists tweet about ( Journalists on Twitter: how do Britain’s news organisations tweet?). Tweetminster maintains separate lists of tweeting journalists for several different media groups, so it was easy to grab the [...]![]()
Regular readers will know how I do quite like to dabble with visual analysis, so here are a couple of doodles with some of the university fees data that is starting to appear. The data set I’m using is a partial one, taken from the Guardian Datastore: Tuition fees 2012: what are the universities charging?. [...]![]()
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