Papers with predicting state-level
What does the language of foods say about us? (D19-62)
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| Challenge: | Using a dataset of 24 million food-related tweets, we can predict if states in the United States are above the median rates for type 2 diabetes mellitus (T2DM) income, poverty, and education are important factors in predicting T2DM rates, but socioeconomic factors do not capture this information. |
| Approach: | They use a dataset of 24 million food-related tweets to investigate the signal contained in the language of food on social media. |
| Outcome: | The language of food can predict health risks, political orientation, and geographic location, and outperform previous work by 4–18%. |