Data is a valuable product for journalists to not only source news stories, but to prove and disprove beliefs. However data on its own is unattractive, and isn’t interesting to a general audience. Instead, visualisations capture the meaning of data, and should present it in such a way that provides understanding, while also making it engaging.
Here are a couple of examples from Instagram, and why I think they’re great visualisations, or perhaps where they’re incomplete.
These two examples from Sky News are about their #OceanRescue campaign. These short, simple video clips animate two statistics very clearly. 40% of plastics in Europe are only used once, and by 2050 the plastic in the oceans would weight more than the fish. Asides from the 40% highlighted in the first clip, they aren’t heavy in numbers. There is nothing more to read, and there is no graph to learn to read or understand. The relevant information is easily accessible.
The colour scheme and overall design also makes it easy to identify these two clips as part of a series, instead of being standalone pieces. The colours are also relevant to the topic: the choice of the colour blue reflecting on the colour of water.
BBC News shared this video, telling the story of Ian and his daughter Claudia, and the differences in their financial situation. It uses an individual human story to tell a national statistical story.
The use of the animation to tell the story makes it simpler to follow, as it gives the ability to integrate numbers and text. The downside to this integration, is that it runs quickly and provides a lot more information than the examples from Sky.
Because video content naturally loops on Instagram, this Guardian example shows a great way of creating content that doesn’t need to have a definitive start and end, like a title card for example.
What lets this example down, is a change of wording between the animation and caption. The animation says that “British office works spend an average of £1,000 a year on…”, where as the caption reads “…totalled more than £1,000 a year”. The caption discredits the animation, as ‘totalling more than’ comes across as a larger increase than perhaps it actually is.
The caption also states that “over the course of a 40-year career, that would amount to about £14,500”, however I work this out to be an average of £360~ per year. Looking into the comments, it appears a previous error has already been corrected by the Guardian, however ensuring the caption and graphic are telling the same story is vital in gaining trust from the audience viewing it.
This second graphic from the Guardian, despite being a graph, is just as clear and easy to read and understand. It is about pasta consumption in different countries, and uses spaghetti pasta to illustrate the kilograms per person against these countries.
The only question this example raises, is a sense of time. Does this graph show consumption over a month, quarter, or year? There is no time scale noted in neither graph or caption, and so it loses its contextual value.
Nicole Yohe hand draws her data visualisations. This particular example shows child soldiers in Africa. The title helps to quickly identify the value of each point, and the labelled axis gives understanding of what you’re reading.
The stick characters give an objective appearance, but their individual scale adds to the ease of reading the graph.
From a readers point-of-view, it is easy to read and understand. As a practitioner, it is very simple to create, and effective in its need to educate and tell a story.
The final example I have is from Clue, a female health and cycle application for mobile devices. Even as a company not involved in news production, the ability to visualise data is still necessary in conveying certain information.
Here, Clue have used the statistics they own to create a quick, worded explanation of an increase in sex drive on valentines day. The colour palette of the image matches that of the brand, giving it identity. The image also uses the application’s logo as part of the design; a clever boost to its identity as well acting as a useful break between two statistics that could otherwise be confused.
The timing of the post is also critical in reaching audiences and being of interest to audiences. A visualisation about sex is appropriate for Valentines Day, just as much as firework related data is for bonfire night, or new year.
What I find works best in data visualisations on Instagram, is simple and short, or still.
The use of animation works good if it is not over complicated, and has very few elements. The hand drawn graphs are a nice illustrative approach, and if including all the necessary information, are just as informative and attractive than the animations.
And finally, whether it’s a video or still image, the caption needs to align with what the audience is reading. If they conflict or confuse each other, then the visualisation isn’t going to work.
Clearly there are not enough data visualisations on Instagram, however with the uptake of news outlets on the social media platform, I don’t think it will be too long before we start to see developing experimentation in this area.