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

Author

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  • Sharon E Alajajian
  • Jake Ryland Williams
  • Andrew J Reagan
  • Stephen C Alajajian
  • Morgan R Frank
  • Lewis Mitchell
  • Jacob Lahne
  • Christopher M Danforth
  • Peter Sheridan Dodds

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.

Suggested Citation

  • Sharon E Alajajian & Jake Ryland Williams & Andrew J Reagan & Stephen C Alajajian & Morgan R Frank & Lewis Mitchell & Jacob Lahne & Christopher M Danforth & Peter Sheridan Dodds, 2017. "The Lexicocalorimeter: Gauging public health through caloric input and output on social media," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-25, February.
    • Handle: RePEc:plo:pone00:0168893
    DOI: 10.1371/journal.pone.0168893
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    References listed on IDEAS

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    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    2. Cynthia Chew & Gunther Eysenbach, 2010. "Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-13, November.
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    Cited by:

    1. Martino Tran & Christina Draeger & Xuerou Wang & Abbas Nikbakht, 2023. "Monitoring the well-being of vulnerable transit riders using machine learning based sentiment analysis and social media: Lessons from COVID-19," Environment and Planning B, , vol. 50(1), pages 60-75, January.
    2. Iacus Stefano M. & Porro Giuseppe & Salini Silvia & Siletti Elena, 2020. "Controlling for Selection Bias in Social Media Indicators through Official Statistics: a Proposal," Journal of Official Statistics, Sciendo, vol. 36(2), pages 315-338, June.

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