Chris Danforth

Professor, Department of Mathematics & Statistics

Computational Story Lab

Vermont Complex Systems Center

University of Vermont


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Research


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“Inside the lab that’s quantifying happiness”
Profile of our research group in Outside Magazine

Research team and group publications

“Is Everybody Doing … OK? Let’s Ask Social Media”
Story on Hedonometer in New York Times

“Has Twitter just had its saddest fortnight ever?”
Story on Hedonometer in Nature

“Instagram photos reveal predictive markers of depression”
Paper in EPJ Data Science, coverage by New York Times

“The emotional arcs of stories are dominated by six basic shapes” Paper in EPJ Data Science, coverage by The Atlantic

“Human language reveals a universal positivity bias”
Paper in PNAS, coverage by New York Times


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Hedonometer: a population scale measure of daily happiness


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StoryWrangler: A visual comparison of phrase popularity in 150 billion tweets


Recent Publications

  • 94. Storywrangler: A massive exploratorium for
    sociolinguistic, cultural, socioeconomic, and political timelines using Twitter.
    T. Alshaabi, J. L. Adams, M. V. Arnold, J. R. Minot, D. R. Dewhurst, A. J. Reagan, C. M. Danforth, P. S. Dodds.
    In Press. Science Advances. 2021.
    [pdf] [arXiv] [website] [thread] [press]

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  • 93. Computational timeline reconstruction of the stories surrounding Trump: Story turbulence, narrative control, and collective chronopathy.
    P. S. Dodds, J. R. Minot, M. V. Arnold, T. Alshaabi, J. L. Adams, A. J. Reagan, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv] [online appendix] [thread]

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  • 92. Generalized Word Shift Graphs: A Method for Visualizing and Explaining Pairwise Comparisons Between Texts.
    R. J. Gallagher, M. R. Frank, L. Mitchell, A. J. Schwartz, A. J. Reagan, C. M. Danforth, P. S. Dodds.
    EPJ Data Science. 2021.
    [pdf] [journal url] [arXiv] [code] [thread]

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  • 91. Quantifying language changes surrounding mental health on Twitter.
    A. M. Stupinski, T. Alshaabi, M. V. Arnold, J. R. Minot, M. Price, P. S. Dodds, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv] [thread]

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  • 90. Gauging the happiness benefit of US urban parks through Twitter.
    A. J. Schwartz, P. S. Dodds, J. P. M. O’Neil-Dunne, T. H. Ricketts, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv] [online appendix] [thread] [blog]

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  • 89. The incel lexicon: Deciphering the emergent cryptolect of a global misogynistic community.
    K. Gothard, D. R. Dewhurst, J. R. Minot, J. L. Adams, M. V. Arnold, T. Alshaabi, A. J. Reagan, C. M. Danforth, P. S. Dodds.
    In Review. 2021.
    [pdf] [arXiv] [thread]

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  • 88. Sirius: A mutual information network tool for exploratory visualization of mixed data
    J. L. Adams, T. F. DeLuca, C. M. Danforth, P. S. Dodds, Y. Zheng, K. Anastasakis, B. Choi, A. Min, M. B. Bessey.
    In Review. 2021.
    [pdf] [arXiv] [thread] [code]

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  • 87. Long-term word frequency dynamics derived from Twitter are corrupted: A bespoke approach to detecting and removing pathologies in ensembles of time series.
    P. S. Dodds, J. R. Minot, M. V. Arnold, T. Alshaabi, J. L. Adams, D. R. Dewhurst, A. J. Reagan, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv] [thread]

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  • 86. Doomscrolling during COVID-19: The negative association between daily social and traditional media consumption and mental health symptoms during the COVID-19 pandemic.
    M. Price, A. C. Legrand, Z. M. F. Brier, K. van Stolk-Cooke, K. Peck, P. S. Dodds, Z. W. Adams, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv]

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  • 85. Local information sources received the most attention from Puerto Ricans during the aftermath of Hurricane Maria.
    B. F. Emery, M. T. Niles, C. M. Danforth, P. S. Dodds.
    PLOS ONE. 2021.
    [pdf] [journal url] [arXiv] [thread]

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  • 84. Interpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance.
    J. R. Minot, N. Cheney, M. Maier, D. C. Elbers, C. M. Danforth, P. S. Dodds.
    In Review. 2021.
    [pdf] [arXiv] [thread]

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  • 83. Divergent modes of online collective attention to the COVID-19 pandemic are associated with future caseload variance.
    D. R. Dewhurst, T. Alshaabi, M. V. Arnold, J. R. Minot, C. M. Danforth, P. S. Dodds.
    In Review. 2020.
    [pdf] [arXiv] [online appendix] [press] [thread]

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  • 82. How the world’s collective attention is being paid to a pandemic: COVID-19 related 1-gram time series for 24 languages on Twitter.
    T. Alshaabi, M. V. Arnold, J. R. Minot, J. L. Adams, D. R. Dewhurst, A. J. Reagan, R. Muhamad, C. M. Danforth, P. S. Dodds.
    PLoS ONE. 2021.
    [pdf] [journal url] [arXiv] [online appendix] [press] [animation] [thread]

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  • 81. Ratioing the President: An exploration of public engagement with Obama and Trump on Twitter.
    J. R. Minot, M. V. Arnold, T. Alshaabi, C. M. Danforth, P. S. Dodds.
    PLoS ONE. 2021.
    [pdf] [journal url] [arXiv] [thread]

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  • 80. Hurricanes and hashtags: Characterizing online collective attention for natural disasters.
    M. V. Arnold, D. R. Dewhurst, T. Alshaabi, J. R. Minot, J. L. Adams, C. M. Danforth, P. S. Dodds.
    PLOS ONE. 2021.
    [pdf] [journal url] [arXiv] [thread]

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  • 79. The growing amplification of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020.
    T. Alshaabi, D. R. Dewhurst, J. R. Minot, M. V. Arnold, J. L. Adams, C. M. Danforth, P. S. Dodds.
    EPJ Data Science. 2021.
    [pdf] [journal url] [arXiv] [online appendix] [thread]

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  • 78. Probability-turbulence divergence: A tunable allotaxonometric instrument for comparing heavy-tailed categorical distributions.
    P. S. Dodds, J. R. Minot, M. V. Arnold, T. Alshaabi, J. L. Adams, D. R. Dewhurst, A. J. Reagan, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv] [online appendix] [thread]

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  • 77. Allotaxonometry and rank-turbulence divergence:
    A universal instrument for comparing complex systems.
    P. S. Dodds, J. R. Minot, M. V. Arnold, T. Alshaabi, J. L. Adams, D. R. Dewhurst, T. J. Gray, M. R. Frank, A. J. Reagan, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv] [online appendix] [code] [thread]

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  • 76. Fame and Ultrafame: Measuring and comparing daily levels of 'being talked about' for United States' presidents, their rivals, God, countries, and K-pop.
    P. S. Dodds, J. R. Minot, M. V. Arnold, T. Alshaabi, J. L. Adams, D. R. Dewhurst, A. J. Reagan, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv] [thread] [online appendix]

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  • 75. The sleep loss insult of Spring Daylight Savings in the US is absorbed by Twitter users within 48 hours.
    K. Linnell, T. Alshaabi, T. McAndrew, J. Lim, P. S. Dodds, C. M. Danforth.
    In Review. 2021.
    [pdf] [arXiv] [thread]

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  • 74. The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong.
    T. Alshaabi, D. R. Dewhurst, J. P. Bagrow, P. S. Dodds, C. M. Danforth.
    PLoS ONE. 2021.
    [pdf] [journal url] [arXiv] [thread]

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  • 73. Chimera States and Seizures in a Mouse Neuronal Model.
    H. Mitchell, M. Mahoney, P. S. Dodds, C. M. Danforth.
    International Journal of Bifurcation & Chaos. 2020.
    [pdf] [journal url] [arXiv] [animation]

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Teaching


Video lectures for recent course on Nonlinear Dynamics available for free on YouTube

Applied Mathematics classes taught at UVM include Linear Algebra, Numerical Analysis, Nonlinear Dynamics, Ordinary Differential Equations, and Data Ethics

We now offer an undergraduate degree in Data Science, as well as both MS and PhD degrees in Complex Systems & Data Science

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Tweets