Papers with predicting state-level

    1 papers
    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%.

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