Lewis Mitchell

Research Interests

Applied Mathematics Applied Statistics Artificial Intelligence Computational Linguistics Computer Communications Networks Computer-Human Interaction Information and Computing Sciences Knowledge Representation and Machine Learning Mathematical Sciences Networking & Telecommunications Networking and Communications Neural, Evolutionary and Fuzzy Computation Neurocognitive Patterns and Neural Networks Numerical and Computational Mathematics Numerical Computation Pattern Recognition and Data Mining Simulation and Modelling Social Sciences Methods Stochastic Analysis and Modelling

Prof Lewis Mitchell

Professor

School of Mathematical Sciences

College of Science

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

My Homepage

I'm a Professor of Data Science 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. Please consult my homepage for further information.

 

Date Position Institution name
2014 - ongoing Lecturer->Professor of Data Science University of Adelaide
2011 - 2014 Ed Lorenz postdoctoral fellow in the mathematics of climate University of Vermont

Date Type Title Institution Name Country Amount
2021 Award JH Michell Medal for outstanding new researchers ANZIAM Australia -
2018 Award ACEMS Recognition for Outstanding Participation in Outreach Award ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) Australia 1000
2018 Award ACEMS Outstanding Achievements Recognition Award ARC Centre of Excellence for Mathematical and Statistical Frontiers Australia 1000
2018 Award SA Young Tall Poppy Award Australian Institute of Policy & Science Australia -
2017 Teaching Award ECMS Faculty Teaching Award (Continuing) University of Adelaide Australia 2000
2017 Honour Fresh Science SA Finallist - - -

Date Institution name Country Title
2008 - 2012 University of Sydney Australia PhD
2003 - 2007 University of Wollongong Australia BMath (Hons) (Adv) / BSc (Physics) (Adv)

Year Citation
2025 Yao, J., Mitchell, L., Maclean, J., & Saratchandran, H. (2025). Data Denoising and Derivative Estimation for Data-Driven Modeling of Nonlinear Dynamical Systems.. CoRR, abs/2509.14219.
2025 Toomes, A., Stringham, O. C., Moncayo, S., Hill, K. G. W., Maher, J., Watters, F., . . . Cassey, P. (2025). The pet trade of native species outside of their natural distributions within Australia is a biosecurity risk. Conservation Science and Practice, 7(1), e13298-1-e13298-14.
DOI Scopus1 WoS1
2025 Cornell, C., Mitchell, L., & Roughan, M. (2025). Vector autoregression in cryptocurrency markets: unraveling complex causal networks. JOURNAL OF COMPLEX NETWORKS, 13(4), 15 pages.
DOI
2025 Wadforth, B., Shahrbabaki, S. S., Strong, C., Karnon, J., Goh, J. S., O’Loughlin, L. P., . . . Ganesan, A. N. (2025). Predicting the spontaneous cardioversion of atrial fibrillation using artificial intelligence–enabled electrocardiography. European Heart Journal: Digital Health, 6(5), 969-978.
DOI
2025 Tonchev, I., Kuklik, P., Tiver, K., Strong, C., Shahrbabaki, S., Chapman, D., . . . Ganesan, A. (2025). Power-Law Distribution of Spatiotemporal Intermittency in Atrial Fibrillation. Heart, Lung and Circulation, 34, S576-S577.
DOI
2025 Murray, C., Mitchell, L., Tuke, J., & Mackay, M. (2025). Probabilistic emotion and sentiment modelling of patient-reported experiences. Artificial Intelligence in Medicine, 167, 103178-1-103178-18.
DOI
2025 Bala, I., Karunarathne, W., & Mitchell, L. (2025). Optimizing Feature Selection by Enhancing Particle Swarm Optimization with Orthogonal Initialization and Crossover Operator. Computers, Materials & Continua, 84(1), 727-744.
DOI Scopus2 WoS2
2025 Kalenkova, A., Mitchell, L., & Roughan, M. (2025). Performance Analysis: Discovering Semi-Markov Models From Event Logs. IEEE Access, 13, 38035-1-38053-19.
DOI Scopus1 WoS1
2024 Dharmaprani, D., Tiver, K., Salari Shahrbabaki, S., Jenkins, E. V., Chapman, D., Strong, C., . . . Ganesan, A. N. (2024). Observable Atrial and Ventricular Fibrillation Episode Durations Are Conformant With a Power Law Based on System Size and Spatial Synchronization. Circulation: Arrhythmia and Electrophysiology, 17(7), 465-475.
DOI Scopus2 WoS2 Europe PMC2
2024 Ho, S. -W., Mitchell, L., & Wang, V. (2024). Modelling Channel Attenuation in Hybrid Optical/E-band System. IEEE Transactions on Wireless Communications, 23(1`2), 18440-18455.
DOI Scopus2
2024 Bala, I., Kelly, T. -L., Lim, R., Gillam, M. H., & Mitchell, L. (2024). An Effective Approach for Multiclass Classification of Adverse Events Using Machine Learning. Journal of Computational and Cognitive Engineering, 3(3), 226-239.
DOI Scopus2
2024 Bala, I., Kelly, T., Stanford, T., Gillam, M. H., & Mitchell, L. (2024). Machine learning-based analysis of adverse events in mesh implant surgery reports. Social Network Analysis and Mining, 14(1, article no. 63), 63-1-63-15.
DOI Scopus2 WoS1
2024 Smart, B., Roughan, M., & Mitchell, L. (2024). The entropy rate of Linear Additive Markov Processes. PLoS One, 19(4), e0295074-1-e0295074-13.
DOI Scopus1 WoS1
2024 Murray, C., Mitchell, L., Tuke, J., & Mackay, M. (2024). Revealing patient-reported experiences in healthcare from social media using thedesign-acquire-process-model-analyse-visualise framework. Digit Health, 10, 1-20.
DOI WoS1
2024 Bala, I., & Mitchell, L. (2024). Thematic exploration of educational research after the COVID pandemic through topic modelling. Journal of Applied Learning & Teaching, 7(1), 26-34.
DOI Scopus4
2023 Dharmaprani, D., Jenkins, E., Quah, J., Tiver, K., Mitchell, L., Tung, M., . . . Ganesan, A. (2023). Spatial autocorrelation dimension as a potential determinant for the temporal persistence of human atrial and ventricular fibrillation.
DOI
2023 Toomes, A., Moncayo, S., Stringham, O. C., Lassaline, C., Wood, L., Millington, M., . . . Cassey, P. (2023). A snapshot of online wildlife trade: Australian e-commerce trade of native and non-native pets. Biological Conservation, 282, 9 pages.
DOI Scopus26 WoS27
2023 Stringham, O. C., Maher, J., Lassaline, C. R., Wood, L., Moncayo, S., Toomes, A., . . . Cassey, P. (2023). The dark web trades wildlife, but mostly for use as drugs. People and Nature, 5(3), 999-1009.
DOI Scopus15 WoS14
2023 Jenkins, E. V., Dharmaprani, D., Schopp, M., Quah, J. X., Tiver, K., Mitchell, L., . . . Ganesan, A. N. (2023). Markov modeling of phase singularity interaction effects in human atrial and ventricular fibrillation.. Chaos, 33(6), 10 pages.
DOI
2023 Dharmaprani, D., Jenkins, E., Tiver, K., Quah, J., Mitchell, L., Tung, M., . . . Ganesan, A. (2023). Fractal Dimension of Atrial and Ventricular Fibrillation: A Potential Determinant for the Persistence and Termination of Cardiac Turbulence. Heart, Lung and Circulation, 32, S196.
DOI
2022 Murray, C., Mitchell, L., Tuke, J., & Mackay, M. (2022). Revealing Patient-Reported Experiences in Healthcare from Social Media using the DAPMAV Framework.. CoRR, abs/2210.04232.
2022 Nasim, M., Weber, D., South, T., Tuke, J., Bean, N. G., Falzon, L., & Mitchell, L. (2022). Are we always in strife? A longitudinal study of the echo chamber effect in the Australian Twittersphere.. CoRR, abs/2201.09161.
2022 Jenkins, E. V., Dharmaprani, D., Schopp, M., Quah, J. X., Tiver, K., Mitchell, L., . . . Ganesan, A. N. (2022). The inspection paradox: An important consideration in the evaluation of rotor lifetimes in cardiac fibrillation.. Front Physiol, 13, 920788.
DOI Scopus4 WoS3 Europe PMC2
2022 Murray, C., Mitchell, L., Tuke, J., & Mackay, M. (2022). Revealing Patient-Reported Experiences in Healthcare from Social Media
using the DAPMAV Framework.
2022 Andreacchio, A., Bean, N., & Mitchell, L. (2022). Modelling Australian Rules Football as spatial systems with pairwise comparisons. Journal of Quantitative Analysis in Sports, 0(0), 215-226.
DOI
2022 Weber, D., Falzon, L., Mitchell, L., & Nasim, M. (2022). Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation. Social Network Analysis and Mining, 12(1), 64-1-64-26.
DOI Scopus7 WoS5 Europe PMC1
2022 Nasim, M., Weber, D., South, T., Tuke, J., Bean, N., Falzon, L., & Mitchell, L. (2022). Are we always in strife? A longitudinal study of the echo chamber effect
in the Australian Twittersphere.
2022 Toomes, A., García‐Díaz, P., Stringham, O. C., Ross, J. V., Mitchell, L., & Cassey, P. (2022). Drivers of the Australian native pet trade: the role of species traits, socioeconomic attributes and regulatory systems. Journal of Applied Ecology, 59(5), 1268-1278.
DOI Scopus22 WoS20 Europe PMC8
2022 Jenkins, E. V., Dharmaprani, D., Schopp, M., Quah, J. X., Tiver, K., Mitchell, L., . . . Ganesan, A. N. (2022). Understanding the origins of the basic equations of statistical fibrillatory dynamics. Chaos: An Interdisciplinary Journal of Nonlinear Science, 32(3), 032101-1-032101-12.
DOI Scopus3 WoS3 Europe PMC3
2022 South, T., Smart, B., Roughan, M., & Mitchell, L. (2022). Information flow estimation: A study of news on Twitter. Online Social Networks and Media, 31, 1-10.
DOI Scopus11 WoS8
2021 Weber, D., Nasim, M., Mitchell, L., & Falzon, L. (2021). Exploring the effect of streamed social media data variations on social network analysis. Social Network Analysis and Mining, 11(1), 62-1-62-38.
DOI Scopus9 WoS7 Europe PMC4
2021 Stringham, O. C., Moncayo, S., Hill, K. G. W., Toomes, A., Mitchell, L., Ross, J. V., & Cassey, P. (2021). Text classification to streamline online wildlife trade analyses.. PloS one, 16(7), 1-12.
DOI Scopus18 WoS16 Europe PMC7
2021 Stringham, O. C., García-Díaz, P., Toomes, A., Mitchell, L., Ross, J. V., & Cassey, P. (2021). Live reptile smuggling is predicted by trends in the legal exotic pet trade. Conservation Letters, 14(6), 10 pages.
DOI Scopus23 WoS24
2021 Stringham, O., Moncayo, S., Thomas, E., Heinrich, S., Toomes, A., Maher, J., . . . Shepherd, C. (2021). Dataset of seized wildlife and their intended uses.
DOI
2021 Dharmaprani, D., Jenkins, E. V., Quah, J. X., Lahiri, A., Tiver, K., Mitchell, L., . . . Ganesan, A. N. (2021). A governing equation for rotor and wavelet number in human clinical ventricular fibrillation: implications for sudden cardiac death. Heart Rhythm, 19(2), 295-305.
DOI Scopus11 WoS11 Europe PMC10
2021 Stringham, O. C., Moncayo, S., Thomas, E., Heinrich, S., Toomes, A., Maher, J., . . . Cassey, P. (2021). Dataset of seized wildlife and their intended uses. Data in Brief, 39, 107531.
DOI Scopus7 WoS5 Europe PMC1
2021 Garrett, P. M., White, J. P., Lewandowsky, S., Kashima, Y., Perfors, A., Little, D. R., . . . Dennis, S. (2021). The acceptability and uptake of smartphone tracking for COVID-19 in Australia.. PloS one, 16(1), 1-23.
DOI Scopus70 WoS61 Europe PMC47
2021 Gallagher, R. J., Frank, M. R., Mitchell, L., Schwartz, A. J., Reagan, A. J., Danforth, C. M., & Dodds, P. S. (2021). Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science, 10(1), 1-29.
DOI Scopus46 WoS36
2021 Zachreson, C., Mitchell, L., Lydeamore, M. J., Rebuli, N., Tomko, M., & Geard, N. (2021). Risk mapping for COVID-19 outbreaks in Australia using mobility data. Journal of the Royal Society Interface, 18(174), 1-11.
DOI Scopus36 WoS33 Europe PMC31
2021 South, T., Roughan, M., & Mitchell, L. (2021). Popularity and centrality in Spotify networks: critical transitions in eigenvector centrality. Journal of Complex Networks, 8(6), 19 pages.
DOI Scopus7 WoS4
2020 Toomes, A., Stringham, O. C., Mitchell, L., Ross, J., & Cassey, P. (2020). Australia's wish list of exotic pets: biosecurity and conservation implications of desired alien and illegal pet species. NEOBIOTA, 60(60), 43-59.
DOI Scopus19 WoS16
2020 Liu, D., Mitchell, L., Cope, R. C., Carlson, S. J., & Ross, J. V. (2020). Elucidating user behaviours in a digital health surveillance system to correct prevalence estimates. Epidemics, 33, 1-7.
DOI Scopus2 WoS1 Europe PMC1
2020 Quah, J., Dharmaprani, D., Lahiri, A., Schopp, M., Mitchell, L., Selvanayagam, J. B., . . . Ganesan, A. N. (2020). Prospective cross-sectional study using Poisson renewal theory to study phase singularity formation and destruction rates in atrial fibrillation (RENEWAL-AF): Study design. Journal of Arrhythmia, 36(4), 660-667.
DOI Scopus5 WoS4 Europe PMC5
2020 Hossny, A. H., Mitchell, L., Lothian, N., & Osborne, G. (2020). Feature selection methods for event detection in Twitter: a text mining approach. Social Network Analysis and Mining, 10(1), 15 pages.
DOI Scopus31 WoS22
2020 Pond, T., Magsarjav, S., South, T., Mitchell, L., & Bagrow, J. P. (2020). Complex contagion features without social reinforcement in a model of social information flow. Entropy, 22(3), 265-1-265--8.
DOI Scopus15 WoS15 Europe PMC6
2020 Dharmaprani, D., Jenkins, E., Aguilar, M., Quah, J. X., Lahiri, A., Tiver, K., . . . Ganesan, A. N. (2020). M/M/infinity birth-death processes - a quantitative representational framework to summarize and explain phase singularity and wavelet dynamics in atrial fibrillation. Frontiers in Physiology, 11, 616866-1-616866-17.
DOI Scopus14 WoS14 Europe PMC14
2020 Stringham, O. C., Toomes, A., Kanishka, A. M., Mitchell, L., Heinrich, S., Ross, J. V., & Cassey, P. (2020). A guide to using the Internet to monitor and quantify the wildlife trade.. Conserv Biol, 35(4), 1130-1139.
DOI Scopus74 WoS66 Europe PMC26
2020 Tuke, J., Nguyen, A., Nasim, M., Mellor, D., Wickramasinghe, A., Bean, N. G., & Mitchell, L. (2020). Pachinko Prediction: A Bayesian method for event prediction from social media data. Information Processing and Management, 57(2), 102147-1-102147-13.
DOI Scopus23 WoS16
2020 Gray, C., Mitchell, L., & Roughan, M. (2020). Bayesian inference of network structure from information cascades. IEEE Transactions on Signal and Information Processing over Networks, 6, 371-381.
DOI Scopus14 WoS10
2020 Roughan, M., Mitchell, L., & South, T. (2020). How the Avengers assemble: ecological modelling of effective cast sizes for movies. PLoS ONE, 15(2), e0223833-1-e0223833-31.
DOI Scopus1 WoS6
2019 Dharmaprani, D., Schopp, M., Kuklik, P., Chapman, D., Lahiri, A., Dykes, L., . . . Ganesan, A. N. (2019). Renewal theory as a universal quantitative framework to characterize phase singularity regeneration in mammalian cardiac fibrillation. Circulation: Arrhythmia and Electrophysiology, 12(12), e007569.
DOI Scopus39 WoS36 Europe PMC36
2019 Gray, C., Mitchell, L., & Roughan, M. (2019). Generating connected random graphs. Journal of Complex Networks, 7(6), 896-912.
DOI Scopus7 WoS4
2019 Bagrow, J., Liu, X., & Mitchell, L. (2019). Information flow reveals prediction limits in online social activity. Nature Human Behaviour, 3(2), 122-128.
DOI Scopus62 WoS46 Europe PMC11
2019 Glonek, M., Tuke, J., Mitchell, L., & Bean, N. (2019). Semi-supervised graph labelling reveals increasing partisanship in the United States Congress. Applied Network Science, 4(1), 62-1-62-18.
DOI Scopus1 WoS1
2018 Cope, R., Ross, J., Chilver, M., Stocks, N., & Mitchell, L. (2018). Connecting surveillance and population-level influenza incidence.
DOI
2018 Venohr, M., Langhans, S. L., Peters, O., Holker, F., Arlinghaus, R., Mitchell, L., & Wolter, C. (2018). The underestimated dynamics and impacts of water-based recreational activities on freshwater ecosystems. Environmental Reviews, 26(2), 199-213.
DOI Scopus74 WoS59
2018 Bagrow, J., & Mitchell, L. (2018). The quoter model: a paradigmatic model of the social flow of written information. Chaos, 28(7), 1-9.
DOI Scopus9 WoS7 Europe PMC4
2018 Tiggemann, M., Churches, O., Mitchell, L., & Brown, Z. (2018). Tweeting weight loss: A comparison of #thinspiration and #fitspiration communities on Twitter. Body Image, 25, 133-138.
DOI Scopus44 WoS39 Europe PMC26
2018 Bellsky, T., & Mitchell, L. (2018). A shadowing-based inflation scheme for ensemble data assimilation. Physica D: Nonlinear Phenomena, 380-381, 1-7.
DOI Scopus1 WoS1
2018 Hossny, A. H., Moschuo, T., Osborne, G., Mitchell, L., & Lothian, N. (2018). Enhancing keyword correlation for event detection in social networks using SVD and k-means: Twitter case study. Social Network Analysis and Mining, 8(1), 1-10.
DOI Scopus12 WoS4
2018 Cope, R., Ross, J., Chilver, M., Stocks, N., & Mitchell, L. (2018). Characterising seasonal influenza epidemiology using primary care surveillance data. PLoS Computational Biology, 14(8), 1006377-1-1006377-21.
DOI Scopus17 WoS15 Europe PMC13
2017 Dodds, P., Dewhurst, D., Hazlehurst, F., Van Oort, C., Mitchell, L., Reagan, A., . . . Danforth, C. (2017). Simon's fundamental rich-get-richer model entails a dominant first-mover advantage. Physical Review E, 95(5), 7 pages.
DOI Scopus11 WoS11 Europe PMC2
2017 Alajajian, S., Williams, J., Reagan, A., Alajajian, S., Frank, M., Mitchell, L., . . . Dodds, P. (2017). The Lexicocalorimeter: gauging public health through caloric input and output on social media. PLoS ONE, 12(2), e0168893-1-e0168893-25.
DOI Scopus21 WoS18 Europe PMC9
2016 Dodds, P., Mitchell, L., Reagan, A., & Danforth, C. (2016). Tracking climate change through the spatiotemporal dynamics of the Teletherms, the statistically hottest and coldest days of the year. PLoS One, 11(5), e0154184-1-e0154184-20.
DOI Scopus6 WoS6 Europe PMC2
2016 Kiley, D., Reagan, A., Mitchell, L., Danforth, C., & Dodds, P. (2016). Game story space of professional sports: Australian rules football. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 93(5), 052314-1-052314-14.
DOI Scopus15 WoS15 Europe PMC5
2016 Reagan, A., Mitchell, L., Kiley, D., Danforth, C., & Dodds, P. (2016). The emotional arcs of stories are dominated by six basic shapes. EPJ Data Science, 5(1), 31-1-31-12.
DOI Scopus308 WoS234
2016 Mitchell, L., & Ross, J. (2016). A data-driven model for influenza transmission incorporating media effects. Royal Society Open Science, 3(10), 160481-1-160481-10.
DOI Scopus29 WoS24 Europe PMC12
2015 Dodds, P. S., Clark, E. M., Desu, S., Frank, M. R., Reagan, A. J., Williams, J. R., . . . Danforth, C. M. (2015). Reply to Garcia et al.: common mistakes in measuring frequency-dependent word characteristics. Proceedings of the National Academy of Sciences of the United States of America, 112(23), E2984-E2985.
DOI Scopus6 WoS4 Europe PMC2
2015 Cody, E., Reagan, A., Mitchell, L., Dodds, P., & Danforth, C. (2015). Climate change sentiment on Twitter: an unsolicited public opinion poll. PLoS One, 10(8), e0136092-1-e0136092-18.
DOI Scopus238 WoS197 Europe PMC41
2015 Dodds, P., Clark, E., Desu, S., Frank, M., Reagan, A., Williams, J., . . . Danforth, C. (2015). Human language reveals a universal positivity bias. Proceedings of the National Academy of Sciences of the United States of America, 112(8), 2389-2394.
DOI Scopus303 WoS269 Europe PMC107
2014 Mitchell, L., & Carrassi, A. (2014). Accounting for model error due to unresolved scales within ensemble Kalman filtering. Quarterly Journal of the Royal Meteorological Society, 141(689), 1417-1428.
DOI Scopus28 WoS28
2014 Frank, M., Mitchell, L., Dodds, P., & Danforth, C. (2014). Standing swells surveyed showing surprisingly stable solutions for the Lorenz '96 model. International Journal of Bifurcation and Chaos, 24(10), 1430027-1-1430027-14.
DOI Scopus13 WoS12
2014 Bellsky, T., Berwald, J., & Mitchell, L. (2014). Nonglobal parameter estimation using local ensemble Kalman filtering. Monthly Weather Review, 142(6), 2150-2164.
DOI Scopus14 WoS13
2013 Frank, M., Mitchell, L., Dodds, P., & Danforth, C. (2013). Happiness and the patterns of life: a study of geolocated tweets. Scientific Reports, 3(1), 2625-1-2625-9.
DOI Scopus123 WoS101 Europe PMC35
2013 Mitchell, L., Frank, M., Harris, K., Dodds, P., & Danforth, C. (2013). The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place. PLoS One, 8(5), e64417-1-e64417-15.
DOI Scopus380 WoS245 Europe PMC103
2013 Mitchell, L., & Gottwald, G. (2013). 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), 212-225.
DOI Scopus4 WoS3
2012 Mitchell, L., & Gottwald, G. (2012). On finite-size Lyapunov exponents in multiscale systems. Chaos, 22(2), 023115-1-023115-9.
DOI Scopus8 WoS7
2012 Mitchell, L., & Gottwald, G. (2012). Data assimilation in slow-fast systems using homogenized climate models. Journal of the Atmospheric Sciences, 69(4), 1359-1377.
DOI Scopus37 WoS36
2011 Gottwald, G., Mitchell, L., & Reich, S. (2011). Controlling overestimation of error covariance in ensemble Kalman filters with sparse observations: a variance-limiting Kalman filter. Monthly Weather Review, 139(8), 2650-2667.
DOI Scopus12 WoS12
2011 Zhu, S., & Mitchell, L. (2011). Combined diffraction and radiation of ocean waves around an OWC device. Journal of Applied Mathematics and Computing, 36(1-2), 401-416.
DOI Scopus12 WoS10
2009 Zhu, S. -P., & Mitchell, L. (2009). Diffraction of ocean waves around a hollow cylindrical shell structure. Wave Motion, 46(1), 78-88.
DOI Scopus37 WoS30

Year Citation
2025 Farina, M., Semmler, C., & Mitchell, L. (2025). Cambridge Analytica's Capability for Influence: Is Manipulation Merely Big Data, Psychological Profiles and Personalised Ads ?. In M. -E. Dowling (Ed.), Digital (Dis)Information Operations Fooling: the Five Eyes (pp. 47-60). Routledge.
DOI
2017 Mitchell, L. (2017). How the internet knows if you’re happy or sad. In J. Watson (Ed.), The Conversation Yearbook 2017: standout articles from Australia's top thinkers. Melbourne, Australia: Melbourne University Press.

Year Citation
2025 Hoang, G. B., Ransom, K. J., Stephens, R., Semmler, C., Fay, N., & Mitchell, L. (2025). A Hybrid Theory and Data-driven Approach to Persuasion Detection with Large Language Models. In Workshop Proceedings of the 19th International AAAI Conference on Web and Social Media (ICWSM 2025) (pp. 1-12). Copenhagen, Denmark: Association for the Advancement of Artificial Intelligence.
DOI
2024 Bala, I., Chauhan, D., & Mitchell, L. (2024). Orthogonally Initiated Particle Swarm Optimization with Advanced Mutation for Real -Parameter Optimization. In PROCEEDINGS OF THE 2024 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2024 COMPANION (pp. 735-738). AUSTRALIA, Melbourne: ASSOC COMPUTING MACHINERY.
DOI WoS3
2024 Bala, I., Chauhan, D., & Mitchell, L. (2024). Orthogonally Initiated Particle Swarm Optimization with Advanced Mutation for Real-Parameter Optimization. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '24) (pp. 735-738). New York, NY: Association for Computing Machinery.
DOI Scopus3
2024 Thomas, J., Hoang, G. B., & Mitchell, L. (2024). Simple models are all you need: Ensembling stylometric, part-of-speech, and information-theoretic models for the ALTA 2024 Shared Task. In Proceedings of the 22nd Annual Workshop of the Australasian Language Technology Association (ALTA 2024) Vol. 22 (pp. 207-212). Canberra, Australia: Association for Computational Linguistics (ACL).
Scopus1
2024 Watt, J., Mitchell, L., & Tuke, J. (2024). Personality Profiling: How informative are social media profiles in predicting personal information?. In ALTA 2024 - Proceedings of the 22nd Annual Workshop of the Australasian Language Technology Association (pp. 153-163). Canberra, Australia: Association for Computational Linguistics (ACL).
2024 Cornell, C., Mitchell, L., & Roughan, M. (2024). Rank Is All You Need: Robust Estimation of Complex Causal Networks. In Studies in Computational Intelligence Vol. 1143 SCI (pp. 468-482). Online: Springer Nature Switzerland.
DOI
2023 Cornell, C., Mitchell, L., & Roughan, M. (2023). Vector Autoregression in Cryptocurrency Markets: Unraveling Complex
Causal Networks.
2023 Watt, J., Tuke, J., & Mitchell, L. (2023). Personality Profiling: How informative are social media profiles in predicting personal information?. In CoRR Vol. abs/2309.13065.
2022 Smart, B., Watt, J., Benedetti, S., Mitchell, L., & Roughan, M. (2022). #IStandWithPutin Versus #IStandWithUkraine: The Interaction of Bots and Humans in Discussion of the Russia/Ukraine War. In Lecture Notes in Computer Science Vol. 13618 LNCS (pp. 34-53). Online: Springer International Publishing.
DOI Scopus24
2021 Murray, C., Mitchell, L., Tuke, S. J., & Mackay, M. (2021). Symptom extraction from the narratives of personal experiences with COVID-19 on Reddit. In Workshop Proceedings of the 15th International AAAI Conference on Web and Social Media (ICWSM 2021) Vol. abs/2005.10454 (pp. 1-10). California, USA: Association for the Advancement of Artificial Intelligence Press.
DOI
2020 Weber, D., Nasim, M., Mitchell, L., & Falzon, L. (2020). A method to evaluate the reliability of social media data for social network analysis. In M. Atzmüller, M. Coscia, & R. Missaoui (Eds.), Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM2020) (pp. 317-321). online: IEEE.
DOI Scopus10 WoS7
2020 Edwards, M., Tuke, S., Roughan, M., & Mitchell, L. (2020). The one comparing narrative social network extraction techniques. In M. Atzmüller, M. Coscia, & R. Missaoui (Eds.), Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM2020) (pp. 905-913). online: IEEE.
DOI Scopus9 WoS5
2020 Mitchell, L., Dent, J., & Ross, J. (2020). Mo’ characters mo’ problems: Online social media platform constraints and modes of communication. In AoIRS Selected Papers of Internet Research Vol. 2018 (pp. 10497-1-10497-5). Montreal, Canada: Association of Internet Researchers.
2020 Weber, D., Nasim, M., Falzon, L., & Mitchell, L. (2020). #ArsonEmergency and Australia's "Black Summer": Polarisation and misinformation on social media. In Proceedings of the 2nd Multidisciplinary International Symposium on Disinformation in Open Online Media (MISDOOM), as published in Lecture Notes in Computer Science Vol. 12259 (pp. 159-173). Switzerland: Springer.
DOI Scopus22
2020 Dennis-Henderson, A., Roughan, M., Mitchell, L., & Tuke, S. (2020). Life still goes on: Analysing Australian WW1 Diaries through Distant Reading. In Proceedings of the 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Barcelona, Spain (Online).
2019 Glonek, M., Tuke, S., Mitchell, L., & Bean, N. (2019). GLaSS: Semi-supervised graph labelling with Markov random walks to absorption. In Proceedings of the 7th International Conference on Complex Networks and Their Applications (COMPLEX NETWORKS 2018), as published in Complex Networks and Their Applications VII: Volume 1 Vol. 812 (pp. 304-315). Cham, Switzerland: Springer.
DOI Scopus1
2019 Mathews, P., Gray, C., Mitchell, L., Nguyen, G., & Bean, N. G. (2019). SMERC: Social media event response clustering using textual and temporal information. In Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 (pp. 3695-3700). online: IEEE.
DOI Scopus2 WoS2
2019 Glenny, V., Tuke, J., Bean, N., & Mitchell, L. (2019). A framework for streamlined statistical prediction using topic models. In Proceedings of the 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature Vol. abs/1904.06941 (pp. 61-70). Minneapolis, MN: Association for Computational Linguistics.
DOI Scopus1
2019 Nguyen, A., South, T., Bean, N., Tuke, S. J., & Mitchell, L. (2019). Podlab at SemEval-2019 Task 3: The Importance of Being Shallow. In Proceedings of the 13th International Workshop on Semantic Evaluation (pp. 292-296). online: The Association for Computational Linguistics.
DOI
2018 Hossny, A., & Mitchell, L. (2018). Event detection in Twitter: A keyword volume approach. In Proceedings of the 2nd International Workshop on Social Computing (IWSC’18) Vol. 2018-November (pp. 1200-1208). Singapore: IEEE.
DOI Scopus28 WoS13
2018 Gray, C. G., Mitchell, L., & Roughan, M. (2018). Super-blockers and the effect of network structure on information cascades. In Proceedings of the 1st International Workshop on Online Social Networks and Media: Network Properties and D ynamics (OSNED 2018), as published in WWW ’18 Companion: The 2018 Web Conference Companion (pp. 1435-1441). New York: Association for Computing Machinery.
DOI Scopus11 WoS10
2018 Nasim, M., Nguyen, A., Lothian, N., Cope, R., & Mitchell, L. (2018). Real-time detection of content polluters in partially observable Twitter networks. In P. -A. Champin, F. L. Gandon, M. Lalmas, & P. G. Ipeirotis (Eds.), Proceedings of the Web Conference 2018, as published in WWW '18 Companion: The 2018 Web Conference (pp. 1331-1339). Lyon, France: ACM.
DOI Scopus20 WoS14
2017 Bagrow, J., Danforth, C., & Mitchell, L. (2017). Which friends are more popular than you? Contact strength and the friendship paradox in social networks. In Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 103-108). online: ACM.
DOI Scopus10
2017 Mathews, P., Mitchell, L., Nguyen, G. T., & Bean, N. G. (2017). The nature and origin of heavy tails in retweet activity. In Proceedings of the 26th International World Wide Web Conference (pp. 1493-1498). Perth, Australia: Association for Computing Machinery.
DOI Scopus20 WoS14
2008 Mitchell, L., & Zhu, S. (2008). Linear diffraction and radiation of surface waves by a hollow suspended cylindrical shell. In Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE Vol. 6 (pp. 579-585). Estoril, PORTUGAL: AMER SOC MECHANICAL ENGINEERS.
DOI

Year Citation
2019 Mitchell, L. (2019). The Hedonometer exhibit (HEDONISM exhibition, MOD) (No. Of Pieces: 5 months) [Exhibition]. MOD (Museum of Discovery), Adelaide.

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

Year Citation
2017 Mitchell, L. (2017). Explainer: how the internet knows if you’re happy or sad. The Conversation.
2016 McVernon, J., Ross, J. V., Glass, K., Mitchell, L., Geard, N., & Moss, R. (2016). Computing helps the study of infections on a global and local scale.
2016 Mitchell, L. (2016). How Twitter gives scientists a window into human happiness and health. The Conversation.

Year Citation
2025 Kalenkova, A., Mitchell, L., & Johnson, E. (2025). Discovering Coordinated Processes From Social Online Networks.
2025 Bala, I., Mitchell, L., & Gillam, M. (2025). Analysis of Voluntarily Reported Data Post Mesh Implantation for Detecting Public Emotion and Identifying Concern Reports.
DOI
2013 Bagrow, J. P., Desu, S., Frank, M. R., Manukyan, N., Mitchell, L., Reagan, A., . . . Bongard, J. C. (2013). Shadow networks: Discovering hidden nodes with models of information
flow.
  • ARC Discovery Project DP210103700: Mathematical modelling of information flow in social networks (with A/Prof Jim Bagrow and Prof. Matthew Roughan) ($390,000 over 3 years)
  • NHMRC Ideas Grant 2002589: Improving the safety of implantable medical devices (with Dr. Marianne Gillam, Dr. Marie-Therese Kelly, Dr. Renly Lim and Dr. Tyman Stanford) ($775,924 over 3 years)
  • ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) (Chief Investigator in 2021)
  • Universities Australia-DAAD (Germany) Australia-Germany Joint Research Cooperation Scheme: Detection and classification of malicious virtual grassroots influence campaigns in social media (with F Neumann, M Nasim, D Weber, C Grimme, H Trautmann, D Assenmacher) ($24,000 over 2 years)
  • Cyber Security CRC: Cyber-social-security during COVID-19: The social media reaction to COVIDSafe ($10,000 over 1 year)
  • DST/University of Adelaide Research agreement: Modelling in the grey zone (with Prof D Stephens)    ($175,000 over 1 year)
  • 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)

 

 

Courses
  • APP MTH 4047 Mathematics of Artificial Intelligence (2022-24)
  • MATHS 2203 Advanced Mathematical Perspectives II (2021,2023-24)
  • APP MTH 3014 Optimisation III (2021-24)
  • MATHS 7027 Mathematical Foundations of Data Science (2019-21)
  • MATHS 1004 Mathematics for Data Science I (2019)
  • APP MTH 3001 Applied Probability III (2018-19)
  • MATHS 2102 Differential Equations II (2015-17)
  • MATHS 2104 Numerical Methods II (2015-17)
  • MBB Mathematics for Biostatistics (online) (2015)
  • MATHS 1011 Mathematics 1A (algebra) (2014)

Date Role Research Topic Program Degree Type Student Load Student Name
2025 Principal Supervisor Understanding Online Influence via the Interplay between Narratives, Social Networks and Online-offline Interactions Master of Philosophy Master Full Time Mr Yi Ren
2025 Co-Supervisor A mathematical modelling framework for examining how social media recommender systems shape user beliefs Doctor of Philosophy Doctorate Full Time Connor Davidson
2025 Principal Supervisor Quantifying Online Persuadability: Analysis, Metrics Development, and Application in Digital Discourse. Doctor of Philosophy Doctorate Full Time Mr Gia Bao Hoang
2025 Principal Supervisor Mixture-of-Experts for Multimodal Synthetic Media Detection Doctor of Philosophy Doctorate Part Time Mr Alessandro Cardoso Laudares Pereira
2024 Principal Supervisor Quantifying the onset of atrial fibrillation as a phase transition from synchrony into chaos Doctor of Philosophy Doctorate Full Time Mr Luke Phillip O'Loughlin
2024 Co-Supervisor Uncertainty Calibration of Probabilistic Machine Learning Models Master of Philosophy Master Full Time Mr Peter Moskvichev
2024 Principal Supervisor Developing explainable AI methods for the financial sector Doctor of Philosophy Doctorate Full Time Mr Wenrui Zhang
2023 Principal Supervisor Applications of data science and artificial intelligence to support intellectual property development in the creative industries Doctor of Philosophy Doctorate Part Time Mr Anton Andreacchio
2023 Principal Supervisor Financial Causality Networks in Cryptocurrency Markets Doctor of Philosophy Doctorate Full Time Mr Cameron Cornell
2022 Co-Supervisor Investigating information flow across multiple online social networks: a network science and information theory approach Doctor of Philosophy Doctorate Full Time Ms Sara Benedetti
2022 Principal Supervisor Identifying and preventing the coordinated spread of misinformation Doctor of Philosophy Doctorate Full Time Mr Scott James Carnie-Bronca
2021 Co-Supervisor Large-scale social media sentiment analysis as a predictor of public behaviour in Australia. Doctor of Philosophy Doctorate Part Time Miss Saranzaya Magsarjav

Date Role Research Topic Program Degree Type Student Load Student Name
2023 - 2025 Co-Supervisor Process Discovery and Classification of User Behaviours in Online Social Networks Master of Philosophy Master Full Time Mr Ethan Michael Johnson
2022 - 2024 Principal Supervisor An Analysis of Bias in Australian Television Media Master of Philosophy Master Full Time Miss Irulan Claire Prowse Murphy
2021 - 2023 Principal Supervisor Measuring and modelling information flows in real-world networks Master of Philosophy Master Full Time Miss Bridget Anna Smart
2021 - 2023 Principal Supervisor The Application of Social Media in Modern-Day Influence Campaigns: Personality Profiling and Information Warfare Master of Philosophy Master Full Time Mr Joshua Watt
2020 - 2023 Co-Supervisor Optimising Battery Replacement in a Fleet of Scooters Master of Philosophy Master Part Time Mr Joshua Thomas Price
2020 - 2022 Co-Supervisor Mathematics of Last-Mile Transportation Master of Philosophy Master Full Time Mr Scott James Carnie-Bronca
2020 - 2025 Principal Supervisor Natural Language Processing Reveals Patient Reported Experiences Doctor of Philosophy Doctorate Full Time Mr Curtis William Murray
2019 - 2021 Co-Supervisor Lagrangian Coherent Data Assimilation for Chaotic Geophysical Systems Master of Philosophy Master Full Time Ms Rose Joy Crocker
2019 - 2021 Principal Supervisor Non-parametric Information Flow Estimation in Social-Media News Master of Philosophy Master Full Time Mr Tobin Max South
2019 - 2021 Co-Supervisor Carmen et Standard Error: Computational Methods in Stylometry for Classical Latin Poetry Master of Philosophy Master Full Time Mr Benjamin Charles Nagy
2018 - 2022 Co-Supervisor Analysing Dynamics of the Illegal Wildlife Trade in Australia Doctor of Philosophy Doctorate Full Time Mr Adam Toomes
2018 - 2020 Principal Supervisor Analysis of World War One Diaries using Natural Language Processing Master of Philosophy Master Full Time Miss Ashley Grace Dennis-Henderson
2018 - 2023 Co-Supervisor Data Science and Usefulness in Domains of Human Action Master of Philosophy Master Part Time Mr Anton Andreacchio
2017 - 2019 Co-Supervisor The One with the Social Network Analysis: The Extraction, Analysis and Modelling of Temporal Social Networks from Narratives Master of Philosophy Master Full Time Miss Michelle Claire Edwards
2017 - 2021 Co-Supervisor Mathematical and Statistical Models of Human Behaviour in Digital Epidemiology Doctor of Philosophy Doctorate Full Time Mr Dennis Liu
2017 - 2019 Co-Supervisor Using Approximate Bayesian Computation and Machine Learning Model Selection Techniques to Understand the Impact of Climate on Seasonal Influenza-like Illness in Australia Master of Philosophy Master Full Time Miss Jessica Penfold
2017 - 2020 Co-Supervisor On the application of Bayesian inference to network estimation problems Doctor of Philosophy Doctorate Full Time Miss Caitlin Miranda Gray
2016 - 2019 Co-Supervisor Characterising the Social Media Temporal Response to External Events Doctor of Philosophy Doctorate Full Time Mr Peter Mathews
2016 - 2018 Co-Supervisor A methodology for predictive topic modelling; or, any excuse to watch Love Actually Master of Philosophy Master Full Time Miss Vanessa Grace Glenny

Date Role Research Topic Location Program Supervision Type Student Load Student Name
2024 - 2024 Principal Supervisor Explainability of machine learning models in credit default prediction The University of Adelaide - Honours - Shufan Wang
2023 - 2023 Principal Supervisor Coordinate networks can outperform Shannon interpolation The University of Adelaide - Honours - Alexander Mackay
2023 - 2023 Co-Supervisor Machine learning for sea ice remote sensing The University of Adelaide - Honours - Elizabeth Shine
2023 - ongoing Co-Supervisor Stochastic process mining The University of Adelaide - Honours - Alexandra Stephenson
2022 - ongoing Co-Supervisor Branching process model of early spread of gene drives through mouse populations The University of Adelaide - Honours - Thomas Heyworth
2018 - 2018 Principal Supervisor Network analysis of communication on Twitter University of Adelaide - Honours - Declan Jamieson
2018 - 2018 Principal Supervisor Analysis of balance in signed social networks from movies University of Adelaide - Honours - Saranzaya (Saka) Magsarjev
2017 - 2019 Co-Supervisor Prediction using emotional arcs in movies University of Adelaide - Honours Part Time Luke Pickering
2016 - 2018 Co-Supervisor Prediction of civil unrest events using Poisson and Hawkes models University of Adelaide - Honours - Wendy Li
2016 - 2016 Principal Supervisor Information cascades on random networks University of Adelaide - Honours - Caitlin Gray

Date Role Committee Institution Country
2017 - ongoing Member School of Mathematical Sciences Outreach Committee - -

Date Role Membership Country
2014 - ongoing Member Australian Mathematical Society Australia

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