Outrageous fake news stories and memes are everywhere online. And, while some are more camouflaged than others, they often use bold fonts and big letters to attract attention.
But when it comes to data visualizations like charts and graphs, it can be harder to tell which are accurate and which are false.
Both the American government and the media have been making bad charts for years. FlowingData.com regularly calls them out when they misrepresent data in graphics, whether it be online or on the air. And, in a study published this year, researchers at Adobe and the University of Illinois at Urbana-Champaign found that people consistently overestimate the impartiality of data visualizations — even when they know that they’re slanted.
So how can journalists and news consumers stay on guard for potentially false or misleading graphics on the internet? Here’s a list of tips.
1. Look for specific words that are intended to incite you. Words like “extreme” and “unfortunate” aren’t scientific and editorialize the data. If they’re included in the title, or even in the body of an accompanying article, that’s a good sign that the chart or graphic you’re looking at might be misconstructed or bogus.
2. Analyze the veracity of the title. Oftentimes the content of a data visualization will be accurate in context, but the title will be completely misleading. Make sure that what the title claims is actually what’s represented in the graphic — and do some Googling to confirm your conclusion.
“When people are assigning some type of atypical or emotional attribute in their title, that is something that, in my opinion, should raise the alarm."
3. Read the axes and data points of a graph. If neither are labeled, or if the Y-axis starts at a number other than zero, there’s a chance that the visualization may be misrepresenting or completely fudging the data. (There are exceptions, of course.)
4. Know who published the graphic first. Do a reverse image search on a visualization to see where else it has appeared in the media and trace it back to its source. If that organization has a specific ideological bent, chances are the graph or chart might not be completely objective. However, it still may be accurate within the given dataset.
“In some cases, it came be helpful to know the framing of the organization that is presenting the information."
5. Try to access the original dataset. If all else fails, you should be able to tell whether or not a graphic is accurately conveying a message by looking at the data that someone used to create it. If you can’t find the provenance of the data, or you can’t confirm it with a quick Google search, think twice before you share it online.
Have a tip that didn’t make the list? Send it to us at firstname.lastname@example.org.