Last Thursday, Facebook’s share price plunged on the news of some not so great numbers from the company on its quarterly earnings report. The data and number itself is not terribly surprising—it is a line chart. But what I loved is how the New York Times handled this on the front of the Business section on Friday morning.
I found the layout of the page and that article striking. In particular, each day of the share price is almost self-contained in that the axis lines start and stop for each day. I question the thickness of the stroke as something a little thinner might have been a bit clearer on the data. However, it might also have not been strong enough to carry the attention at the top of the page. As it is, that attention is needed to draw the reader down the page and then down across the fold.
Additionally, the designers were sensitive to the need to draw that attention down the page. In order to do that they kept the white space around the graphic and kept the text to two small blocks before moving on to the interior of the section.
Credit for the story goes to Matthew Philips. Although I’m pretty sure the page layout goes to somebody else.
Let’s aim for something a bit lighter today. Well, lighter in all things but calories, perhaps. Today we have a piece from the Wall Street Journal that looks at the social media presence of several large fast food brands. Overall, it has a few too many gimmicky illustrations for my comfort. But, the strength of the piece is that it does look at some real data, e.g. plotted Twitter response rates, and then contextualises it with appropriate callouts.
The illustrations are killing me, though.
Credit for the piece goes to Marcelo Prince and Carlos A. Tovar.
Earlier this week, Wolfram Alpha released some findings from its analytics project on Facebook. While the results offer quite a bit to digest, the use of some data visualisation makes it a little bit easier. And a lot more interesting.
The results offer quite a bit of detail on interests, relationship statuses, geographic locations, and ages. Below is just one of the small multiple sets, this one looks at the number of friends of different ages for people of different ages. Basically, how many young or old people are friends of young people? Friends of old people?
But I was most interested in the analysis of social networks. The mosaic below is indicative of the sheer size of the survey, but also begins to hint at the variance in the social structures of the data donors.
While these views are all neat, where it begins to get really interesting is Wolfram Alpha’s work on classifying the different types of social networks. By aggregating and averaging out clusters, simple forms begin to emerge. And after those forms emerged, they were quantified and the results are a simple bar chart showing the distribution of the different types of networks.
Overall, some very interesting work. But one might naturally wonder how their own networks are structured. Or just be curious to look at the data visualisation of their own Facebook profile. Or maybe only some of us would. Fortunately, you still can link your account to a Wolfram Alpha account (you have to pay for advanced features, however) and get a report. Below is the result of my network, for those who know me semi-well I have labelled the different clusters to show just how the clustering works.