The Twitter Diet

How does food (or talking about food online) relate to how happy you are? This is part 3 of our series on the Geography of Happiness. Previously we’ve looked at how happiness varies across the United States (as measured from word frequencies in geotagged tweets), and then at how different socioeconomic factors relate to variations in happiness. Now we focus in on one particular important health factor that might influence happiness, obesity.

We looked at how happiness varied with obesity across the 190 largest metropolitan statistical areas in the United States, giving us the following scatter plot:

happinessObesity

Each point represents one city; for example the city with both(!) lowest obesity and greatest happiness in this set is Boulder, CO, located at the top left. The red line is a linear trend through the data (a line of best fit). Again, for the mathematically minded onehappybird watchers, we show the Spearman correlation coefficient and its corresponding p-value at the lower left. We do this to convince you that there is, in fact, a statistically significant downward trend in the blob of points in the picture! The big story here is of course that as obesity goes up, happiness goes down.

The natural next question to ask is: are there any words which could be indicators of obesity? What foods are people in obese cities eating, or talking about? To answer this question we correlated word frequencies with obesity, and searched for the most strongly-correlating food-related words. Below are two examples: on the left, “mcdonalds”, and on the right, “cafe”.

cafeMcDonalds

As obesity goes up, so does talk (at least on Twitter) about McDonalds, but talk about cafes follows the opposite trend! Does that mean that in order to lose weight we should spend more time sipping lattes in cafes? I wish.

Looking through the list of words, the top 5 food-related words that increase in frequency as obesity went up were:

  1. mcdonalds
  2. eat
  3. wings
  4. hungry
  5. heartburn

We were surprised by ‘hungry’! On the other hand, the top food-related words which were used more as obesity went down were:

  1. cafe
  2. sushi
  3. brewery
  4. restaurant
  5. bar

Perhaps unsurprisingly, these are words typically used by the high-socioeconomic group described in our previous post on city happiness, suggesting that better health correlates with higher socioeconomic status. You can find the complete list of how all words correlate with happiness here (page best viewed using Google Chrome). One surprising result was the observation that far more food-related words appeared in the low-obesity group than in the high-obesity group; in other words, food was being talked about more in the less-obese cities!

Summarizing: based on word usage, the Twitter diet consists of: breakfast at your favorite cafe, a delicious sushi lunch, dinner out at a fancy restaurant, with a nightcap at the best local bar or brewery. Thank you Twitter, don’t mind if I do.

All jokes aside, this sort of technique has great potential. Imagine being able to predict whether obesity was going to rise or fall in a city, or estimate changes in other demographics, just by analyzing the words people use online. Perhaps New York City Mayor Michael Bloomberg would find some early indicators of the success or failure of his war on soda!

And that’s all for this series of posts on the geography of happiness. More information on all of the results in this series can be found in our recently submitted arxiv paper. Please take a look at it and the accompanying online appendices, where you can look through all of the data yourself. As a special bonus feature, you can check out this video of me talking about this work at our recent TEDxUVM conference.  Thanks for reading!