Can Your Mood Affect Your Ability to Interpret Data?


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Ever notice that when you’re in a bad mood, you tend to make more mistakes? You stub your toe, fumble your cell phone, or misdial a number. According to a recent study from Tufts, your mood can also affect your visual judgement, particularly your ability to effectively interpret data visualizations.

In the study, researchers used affective priming, a method of manipulating participants’ moods negatively or positively, by having participants read a certain type of news article that would influence their mood. After they read the article, participants were given visualizations to interpret. Results showed that those who were positively primed made less errors in interpreting the data.

Can Your Mood Affect Your Ability to Interpret Data?Study results show visualization comprehension for participants who were negatively and positively primed.

While it appeared that a good mood increased the ability to interpret the visualizations correctly, researchers were careful to note that a negative mood did not decrease the ability to interpret visualizations.

So, what does that mean for us data visualization professionals? Can a lighthearted intro to an infographic help readers engage better with the content? Probably not. The study examined participants who were successfully primed in the desired direction (positive or negative), which turned out to be only 30% of the original sample. With so many emotional variables and influences, manipulating user moods is more difficult in everyday applications.

Still, the study points to future implications and new questions to answer in terms of how we interact with and comprehend data and visual content.

  • If positive priming proves to be a legitimate tool after further research, how can designers incorporate it into their visualizations?
  • For those designing visualization tools, could the environments in which users interact with a system affect comprehension? As the researchers note, “a user in a disaster-response setting may be more subject to negative priming, whereas a user in gaming may be more subject to positive priming.”
  • If the visualization itself is likely to trigger a strong emotional reaction (e.g., survival rates for a controversial medical procedure you’re about to undergo), how do you ensure that data is accurately understood?
  • And how do negative or positive emotions impact other cognitive processes?

There is plenty more to discover in this field, and although we can’t preach positive priming quite yet, we’re excited to see these questions explored. Then again, we might already be biased: Data always makes us happy.

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