I'm a Senior Lecturer in Applied Mathematics at the University of Adelaide. I study how information moves over social networks using mathematical models, coupled with data science techniques. My research interests are in computational social science, human dynamics, online social networks, as well as data assimilation and the mathematics of weather and climate.

My CV (October 2020)

Email: lewis.mitchell@adelaide.edu.au
Phone: +61 8 8313 5424

Ingkarni Wardli 6.46
School of Mathematical Sciences
North Terrace Campus
The University of Adelaide
SA 5005 Australia


[My Google Scholar citations]

Published articles

  1. C. Gray, L. Mitchell, and M. Roughan.
    Bayesian Inference of Network Structure From Information Cascades.
    IEEE Transactions on Signal and Information Processing over Networks, 6: 371-81, 2020.
    [arXiv version]

  2. T. Pond, S. Magsarjav, T. South, L. Mitchell, and J. P. Bagrow.
    Complex contagion features without social reinforcement in a model of social information flow.
    Entropy, 22(3): 265, 2020.

  3. D. Liu, L. Mitchell, R. C. Cope, S. J. Carlson, and J. V. Ross.
    Elucidating user behaviours in a digital health surveillance system to correct prevalence estimates.
    Epidemics, 33: 100404, 2020.

  4. M. Roughan, L. Mitchell, and T. South.
    How the Avengers assemble: Ecological modelling of effective cast sizes for movies.
    PLoS ONE, 15(2): e0223833, 2020.

  5. J. Tuke, A. Nguyen, M. Nasim, D. Mellor, A. Wickramasinghe, N. G. Bean, and L. Mitchell.
    Pachinko Prediction: A Bayesian method for event prediction from social media data.
    Information Processing and Management, 57(2), 102147, 2020.
    [arXiv version]

  6. J. P. Bagrow, X. Liu, and L. Mitchell.
    Information flow reveals prediction limits in online social activity.
    Nature Human Behaviour, 3: 122–128, 2019.
    [arXiv version]

  7. C. Gray, L. Mitchell, and M. Roughan.
    Generating Connected Random Graphs.
    Journal of Complex Networks, cnz011, doi:10.1093/comnet/cnz011, 2019.
    [arXiv version] [github]

  8. M. Glonek, J. Tuke, L. Mitchell, and N. Bean.
    Semi-supervised graph labelling reveals increasing partisanship in the United States Congress.
    Applied Network Science, 4 (1), 62, 2019.

  9. D. Dharmaprani, M. Schopp, P. Kuklik, D. Chapman, A. Lahiri, L. Dykes, F. Xiong, M. Aguilar, B. Strauss, L. Mitchell, K. Pope, C. Meyer, S. Willems, F. G. Akar, S. Nattel, A. D. McGavigan, A. N. Ganesan.
    Renewal Theory as a Universal Quantitative Framework to Characterize Phase Singularity Regeneration in Mammalian Cardiac Fibrillation.
    Circulation: Arrhythmia and Electrophysiology, 12(12):e007569, 2019.
    [bioRxiv version]

  10. A. Nguyen, T. South, N. Bean, J. Tuke, and L. Mitchell.
    Podlab at SemEval-2019 Task 3: The Importance of Being Shallow.
    Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval '19), 292-296, 2019.

  11. V. Glenny, J. Tuke, N. Bean, and L. Mitchell.
    A framework for streamlined statistical prediction using topic models.
    Proceedings of the 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, 61-70, 2019.
    [arXiv version]

  12. R. C. Cope, J. V. Ross, M. Chilver, N. P. Stocks, and L. Mitchell.
    Characterising seasonal influenza epidemiology using primary care surveillance data.
    PLoS Computational Biology, 14(8): e1006377, 2018.

  13. J. P Bagrow and L. Mitchell.
    The quoter model: A paradigmatic model of the social flow of written information.
    Chaos, 28: 075304, 2018.
    [arXiv version]

  14. M. Glonek, J. Tuke, L. Mitchell, and N. Bean.
    GLaSS: Semi-supervised graph labelling with Markov random walks to absorption.
    COMPLEX NETWORKS 2018: Complex Networks and Their Applications VII, 304-15, 2018.

  15. P. Mathews, C. Gray, L. Mitchell, G. T. Nguyen, and N. G. Bean.
    SMERC: Social media event response clustering using textual and temporal information.
    Proceedings of the 2018 International Workshop on Big Social Media Data Management and Analysis (BSMDMA2018), 2018.

  16. T. Bellsky and L. Mitchell.
    A shadowing-based inflation scheme for ensemble data assimilation.
    Physica D, doi: 10.1016/j.physd.2018.05.002, 2018.
    [arXiv version]

  17. A. Hany Hossny, T. Moschou, G. Osborne, L. Mitchell, and N. Lothian.
    Enhancing keyword correlation for event detection in social networks using SVD and k-means: Twitter case study.
    Social Network Analysis and Mining, 8: 49, 2018.
    [arXiv version]

  18. C. Gray, L. Mitchell, and M. Roughan.
    Super-blockers and the effect of network structure on information cascades.
    Proceedings of the 26th International Conference on the World Wide Web (WWW '18) Companion, 1435-1441, 2018.
    [arXiv version]

  19. M. Nasim, A. Nguyen, N. Lothian, R. C. Cope, and L. Mitchell.
    Real-time detection of content polluters in partially observable Twitter networks.
    Proceedings of the 26th International Conference on the World Wide Web (WWW '18) Companion, 1331-1339, 2018.
    [arXiv version]

  20. M. Tiggemann, O. Churches, L. Mitchell, and Z. Brown.
    Tweeting weight loss: A comparison of #thinspiration and #fitspiration communities on Twitter.
    Body Image, 25: 133-138, 2018.

  21. M. Venohr, S. L. Langhans, O. Peters, F. Holker, R. Arlinghaus, L. Mitchell, and C. Wolter.
    The underestimated dynamics and impacts of water-based recreational activities on freshwater ecosystems.
    Environmental Reviews, 26(2): 199-213, 2018.

  22. A. Hany Hossny and L. Mitchell.
    Event detection in Twitter: A keyword volume approach.
    2018 IEEE International Conference on Data Mining Workshops (ICDMW), Singapore, 1200-1208, 2018.
    [arXiv version]

  23. J. P. Bagrow, C. M. Danforth, and L. Mitchell.
    Which friends are more popular than you? Contact strength and the friendship paradox in social networks.
    Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM '17), 2017.

  24. P. Mathews, L. Mitchell, G. Nguyen and N. G. Bean.
    The nature and origin of heavy tails in retweet activity.
    Proceedings of the 26th International Conference on the World Wide Web (WWW '17) Companion, pp. 1493-1498, 2017.

  25. P. S. Dodds, D. R. Dewhurst, F. F. Hazlehurst, C. M. Van Oort, L. Mitchell, A. J. Reagan, J. R. Williams, and C. M. Danforth.
    Simon's fundamental rich-gets-richer model entails a dominant first-mover advantage.
    Physical Review E, 95: 052301, 2017.
    [arxiv version]

  26. S. E. Alajajian, J. R. Williams, A. J. Reagan, S. C. Alajajian, M. R. Frank, L. Mitchell, J. Lahne, C. M. Danforth, and P. S. Dodds.
    The Lexicocalorimeter: Gauging public health through caloric input and output on social media.
    PLoS ONE, 12(2): e0168893, 2017.
    [Online appendices]

  27. L. Mitchell and J. V. Ross.
    A data-driven model for influenza transmission incorporating media effects.
    Royal Society Open Science, 3: 160481, 2016.

  28. A. Reagan, L. Mitchell, D. Kiley, C. M. Danforth, and P. S. Dodds.
    The emotional arcs of stories are dominated by six basic shapes.
    EP J Data Science, 5(1): 31, 2016.

  29. P. S. Dodds, L. Mitchell, A. Reagan, and C. M. Danforth.
    Tracking Climate Change through the Spatiotemporal Dynamics of the Teletherms, the Statistically Hottest and Coldest Days of the Year.
    PLoS ONE, 11(5): e0154184, 2016.
    [Online appendices] [Twitter account]

  30. D. P. Kiley, A. J. Reagan, L. Mitchell, C. M. Danforth, and P. S. Dodds.
    Game story space of professional sports: Australian Rules Football.
    Physical Review E, 93: 052314, 2016.
    [arXiv version]

  31. E. M. Cody, A. J. Reagan, L. Mitchell, P. S. Dodds, and C. M. Danforth.
    Climate change sentiment on Twitter: An unsolicited public opinion poll.
    PLoS ONE, 10(8): e0136092, 2015.

  32. P. S. Dodds, E. M. Clark, S. Desu, M. R. Frank, A. J. Reagan, J. R. Williams, L. Mitchell, K. D. Harris, I. M. Kloumann, J. P. Bagrow, K. Megerdoomian, M. T. McMahon, B. F. Tivnan, and C. M. Danforth.
    Human language reveals a universal positivity bias.
    PNAS, 111(8): 2389-2394, 2015.
    [Online appendices] [Reply to Garcia et al.: Common mistakes in measuring frequency dependent word characteristics]

  33. L. Mitchell and A. Carrassi.
    Accounting for model error due to unresolved scales within ensemble Kalman filtering.
    Quarterly Journal of the Royal Meteorological Society, 141(689): 1417-1428, 2014.
    [arXiv version]

  34. T. Bellsky, J. Berwald and L. Mitchell.
    Non-global parameter estimation using local ensemble Kalman filtering.
    Monthly Weather Review, 142 (6), pp. 2150–2164, 2014.

  35. M. R. Frank, L. Mitchell, P. S. Dodds and C. M. Danforth.
    Standing swells surveyed showing surprisingly stable solutions for the Lorenz 96 Model.
    International Journal of Bifurcations and Chaos, 24(10): 1430027, 2014.

  36. L. Mitchell, M. R. Frank, K. D. Harris, P. S. Dodds and C. M. Danforth.
    The Geography of Happiness: Connecting Twitter sentiment and expression, demographics, and objective characteristics of place.
    PLoS ONE, 8(5): e64417, 2013.
    [arXiv version] [Online appendices]

  37. M. R. Frank, L. Mitchell, P. S. Dodds and C. M. Danforth.
    Happiness and the patterns of life: A study of geolocated tweets.
    Scientific Reports, 3: 2625, 2013.

  38. L. Mitchell and G. A. Gottwald.
    Controlling model error of underdamped forecast models in sparse observational networks using a variance limiting Kalman filter.
    Quarterly Journal of the Royal Meteorological Society, 139 (670), pp. 212-225, 2013.

  39. L. Mitchell and G. A. Gottwald.
    On finite-size Lyapunov exponents in multiscale systems.
    Chaos, 22 (2), 023115, 2012.

  40. L. Mitchell and G. A. Gottwald.
    Data assimilation in slow-fast systems using homogenized climate models.
    Journal of the Atmospheric Sciences, 69 (4), pp. 1359-1377, 2012.

  41. G. A. Gottwald, L. Mitchell and S. Reich.
    Controlling error overestimation of error covariance in ensemble Kalman filters with sparse observations: A variance-limiting Kalman filter.
    Monthly Weather Review, 139 (8), pp. 2650-2667, 2011.
    [arXiv version]

  42. S.-P. Zhu and L. Mitchell.
    Combined diffraction and radiation of ocean waves around an OWC device.
    Journal of Applied Mathematics and Computing, 36 (1-2), pp. 401-416, 2010.

  43. S.-P. Zhu and L. Mitchell.
    Diffraction of ocean waves around a hollow cylindrical shell structure.
    Wave Motion, 46 (1), pp. 78-88, 2009.


  • R. C. Cope, J. V. Ross, M. Chilver, N. P. Stocks, and L. Mitchell.
    Connecting surveillance and population-level influenza incidence (submitted), 2018.

  • M. Edwards, L. Mitchell, J. Tuke, and M. Roughan
    The one comparing narrative social network extraction techniques (submitted), 2018.

  • M. R. Frank, J. R. Williams, L. Mitchell, J. P. Bagrow, P. S. Dodds, and C. M. Danforth.
    Constructing a taxonomy of fine-grained human movement and activity motifs through social media, 2014.

  • J. P. Bagrow, S. Desu, M. R. Frank, N. Manukyan, L. Mitchell, A. Reagan, E. E. Bloedorn, L. B. Booker, L. K. Branting, M. J. Smith, B. F. Tivnan, C. M. Danforth, P. S. Dodds, and J. C. Bongard.
    Shadow networks: Discovering hidden nodes with models of information flow, 2013.

  • Selected short articles, blog posts, etc

  • L. Mitchell. Explainer: how the internet knows if you’re happy or sad. The Conversation, May 2017.
    [Selected for The Conversation Yearbook 2017]

  • L. Mitchell. How Twitter gives scientists a window into human happiness and health. The Conversation, July 2016.

  • J. McVernon, J. V. Ross, K. Glass, L. Mitchell, N. Geard, R. Moss. Computing helps the study of infections on a global and local scale. The Conversation, June 2016.

  • Where is the happiest city in the USA? Blog post, compstorylab.org, February 2013.

  • L. Mitchell. Using statistical data to improve weather forecasting. Gazette of the Australian Mathematical Society, 37 (4), pp. 242-243, 2010.

  • L. Mitchell and S.-P. Zhu. Linear diffraction and radiation of surface waves by a hollow suspended cylindrical shell. Proceedings of the ASME 27th International Conference on Offshore Mechanics and Arctic Engineering (OMAE 2008), June 2008.

  • Grants

  • Centre for Invasive Species Solutions: Understanding and intervening in illegal trade in non-native species (with Prof. Joshua Ross and A/Prof. Phill Cassey) ($665,000 over 3 years)
  • Data to Decisions CRC Beat The News Project: Predicting common and novel disease outbreaks by assimilating open data into epidemiological models (with A/Prof. Joshua Ross and Prof. Nigel Bean) ($637,606 over 3 years)
  • Data to Decisions CRC Beat The News Project: Predicting civil unrest and election outcomes using Bayesian network models (with Dr. Jonathan Tuke and Prof. Nigel Bean) ($661,261 over 3 years)

  • Talks, media and more

    Selected talks

  • Big Happy: Revealing the character of cities through data (TEDx talk).
    TEDxUVM, Burlington VT, October 2012.
  • Selected media

  • The case of the fear chase.
    The School of Batman podcast, April 2018.
  • How social media companies are figuring out how you feel.
    ABC Radio, RN Drive. May 24, 2017.
  • Story arcs in fiction according to artificial intelligence.
    ABC Radio, Books and Arts program. May 22, 2017.
  • Great Literature Is Surprisingly Arithmetic.
    Scientific American. February 2017.
  • Twitter can tell which states love jogging and which are eating hot dogs.
    Washington Post. July 29, 2015.
  • Does langauge work to make the world a happier place?
    Cosmos Magazine. February 16, 2015.
  • Language proves we're all optimists at heart.
    ABC News in Science. February 10, 2015.
  • The Happiest States In America In One Map (INFOGRAPHIC).
    Huffington Post. August 2, 2013.
  • Twitter study: Happiness rises the further you travel.
    BBC Future. April 11, 2013.
  • New Study Uses Tweets To Rank America’s Happiest Cities, States.
    Time Magazine Online. February 25, 2013.
  • The geography of happiness according to 10 million tweets.
    The Atlantic. February 19, 2013.
  • Other:

  • I won a Tall Poppy Award and they made a cool short video about me, check it out!
  • hedonometer.org, a project from the University of Vermont's Computational Story Lab tracking daily happiness online.
    The Map section is inspired by my Geography of Happiness paper. Tweet any interesting trends you discover!
  • compstorylab.org, the Computational Story Lab's blog (I have some blog posts here).
  • The online appendices for our paper on the universal positivity bias across languages allows you to explore the "shape of stories" (a la Kurt Vonegut) for a number of classic novels. You also explore the emotional trajectories of over 1000 different movies.