When the Graph Lies: Misleading Online Data Visualizations

Recently, amidst the sea of Instagram infographics plaguing my feed, and in light of an unprecedented rapidly-approaching summer, I’ve noticed a number of misleading graphs claiming global temperatures haven’t increased or that climate change isn’t real. One graph in particular caught my eye, showing average global temperatures from 1998 to 2010, with the y-axis so dramatically truncated that the differences looked almost nonexistent. This was alarming and frustrating, to say the least.

The purpose of this manipulated data was likely to underreport the urgency of climate change by cherry-picking a short time frame and visually skewing temperature increases. By doing so, the creator could make viewers doubt scientific research and consensus, perhaps to advance a political agenda or simply farm engagement through inflammatory content.
The graph tricked viewers in many ways, but the most disturbing was the bold and misleading caption shared along with the graphic: “Global warming has paused. Check your scientists!” This tactic relies on people skimming the post rather than analyzing the data for themselves, and makes the graph seem authoritative despite the fact that it misrepresents reality.

However, there are several ways to determine whether graphs like these are accurate. First, you can check the original data sources. In this case, organizations like NASA and the IPCC provide full, comprehensive datasets and clear data visualization so that you can draw conclusions for yourself. Second, examine the time frame and axes, for graphs specifically. Dramatically short or long periods of time, and severely truncated or exaggerated axes, are some of the most common aspects of misleading graphs. Finally, compare with other graphs that illustrate the same information to determine if the trends align.

Understanding how common and accessible data manipulation is in today’s digital world is essential. Yet, by questioning graphs, checking sources, and approaching digital media with a degree of skepticism, we can avoid being misled and help others in recognizing when the data may not be what it seems.