The Lexicocalorimeter: Gauging public health through caloric input and output on social media

TL;DR

The Lexicocalorimeter is an innovative tool that analyzes social media text to estimate population caloric input and output, providing real-time insights into public health and well-being.

Contribution

It introduces a novel, interpretable method for measuring population health through social media language analysis using caloric-related phrase scoring.

Findings

Strong correlation with health and well-being metrics

Outperforms individual caloric measures in some cases

Capable of real-time health signal detection

Abstract

We propose and develop a Lexicocalorimeter: an online, interactive instrument for measuring the "caloric content" of social media and other large-scale texts. We do so by constructing extensive yet improvable tables of food and activity related phrases, and respectively assigning them with sourced estimates of caloric intake and expenditure. We show that for Twitter, our naive measures of "caloric input", "caloric output", and the ratio of these measures are all strong correlates with health and well-being measures for the contiguous United States. Our caloric balance measure in many cases outperforms both its constituent quantities, is tunable to specific health and well-being measures such as diabetes rates, has the capability of providing a real-time signal reflecting a population's health, and has the potential to be used alongside traditional survey data in the development of public policy and collective self-awareness. Because our Lexicocalorimeter is a linear superposition of principled phrase scores, we also show we can move beyond correlations to explore what people talk about in collective detail, and assist in the understanding and explanation of how population-scale conditions vary, a capacity unavailable to black-box type methods.