Recent Publications

2024

• Derecki, R., O’Shea, B. & Goulding, J. (2024). Leveraging multiple digital footprint datasets to predict racial, sex-based, and sexual-orientation bias across US states. International Journal of Population Data Science, 9(4).
• Liziniewicz, B., Harvey, J., Goulding, J. & Dowthwaite, L. (2024). Digital footprints as means of measuring loneliness experience and embeddedness in social networks for designing digital mental health interventions. International Journal of Population Data Science, 9(4).
• Milligan, G., Nica-Avram, G., Harvey, J. & Goulding, J. (2024). Foodinsecurity.london: Developing a food-insecurity prevalence map for London – a machine learning from food-sharing footprints. International Journal of Population Data Science, 9(4).
• Semple, T., Harvey, J., Rodrigues, L., Gillott, M., Figueredo, G. & Nica-Avram, G. (2024). Utilising User Data from a Food-Sharing App to Evidence the ‘Heat-or-Eat’ Dilemma. International Journal of Population Data Science, 9(4).
• Maliehe, K., Goulding, J., Alam, S. & Marsh, S. (2024). Earth Observations, Digital Footprints and Machine-Learning: Greenhouse Gas Stocktaking for Climate Change Mitigation. International Journal of Population Data Science, 9(4).
• Poon, N., Haworth, C., Dolan, E. & Skatova, A. (2024). Studying Health and Illness Experience using Linked Data (SHIELD): Empowering customers to donate shopping data for chronic pain research. International Journal of Population Data Science, 9(4).
• Makokoro, K., Long, G., Harvey, J., Smith, A., Welham, S., Lukinova, E. & Goulding, J. (2024). Predicting Healthy Start Scheme Uptake using Deprivation and Food Insecurity Measures. International Journal of Population Data Science, 9(4).
• Milligan, G., Bernard, A., Dowthwaite, L., Vallejos, E. P., Davis, J., Salhi, L., & Goulding, J. (2024). Developing a single‐session outcome measure using natural language processing on digital mental health transcripts. Counselling and Psychotherapy Research.
• Trodd, Z., Waite, C., Goulding, J., & Boyd, D. S. (2024). Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset. Societies, 14(5), 62.
• Semple, T., Rodrigues, L., Harvey, J., Figueredo, G., Nica-Avram, G., Gillott, M., Milligan, G. & Goulding, J. (2024). An empirical critique of the low income low energy efficiency approach to measuring fuel poverty. Energy Policy, 186, 114014.
• Mansilla, R., Long, G., Welham, S., Harvey, J., Lukinova, E., Nica-Avram, G., Smith, G., Salt, D., Smith, A. & Goulding, J. (2024). Detecting iodine deficiency risks from dietary transitions using shopping data. Scientific Reports, 14, 1017.

2023

• Dolan, E., Goulding, J., Marshall, H., Smith, G., Long, G., & Tata, L. J. (2023). Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models. Nature Communications, 14(1), 7258.
• Dolan, E. H., Goulding, J., Tata, L. J., & Lang, A. R. (2023). Using Shopping Data to Improve the Diagnosis of Ovarian Cancer: Computational Analysis of a Web-Based Survey. JMIR cancer, 9(1), e37141.
• Huntington, B., Goulding, J., & Pitchford, N. J. (2023). Pedagogical features of interactive apps for effective learning of foundational skills. British Journal of Educational Technology.
• Poorrezaei, M., Pich, C., Armannsdottir, G., Branco-Illodo, I., & Harvey, J. (2023). Exploring young voter engagement and journey mapping across political events. International Journal of Market Research, 14707853231151890. 
• Harvey, J., Long, G., Mansilla, R., Welham, S., Rose, P., Thomas, M., Milligan, G., Dolan, E., Parkes, J., Goulding, J. (2023), Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake. In 2023 IEEE International Conference on Big Data.
• Milligan, G., Harvey, J., Dowthwaite, L., Vallejos, E. P., Nica-Avram, G., & Goulding, J. (2023). Assessing relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data. In 2023 IEEE International Conference on Big Data.
• Huntington, B., Pitchford, N., & Goulding, J. (2023). Education for out-of-school children: Unpacking driving factors of vulnerability via digital-learning footprint data in East Africa. International Journal of Population Data Science, 8(3).
• Long, G., Nica-Avram, G., Harvey, J., Mansilla, R., Welham, S., Lukinova, E., & Goulding, J. (2023). Predicting health related deprivation using loyalty card digital footprints. International Journal of Population Data Science, 8(3).
• Skatova, A., Stewart, N., Flavahan, E., & Goulding, J. (2023). Daily, Weekly and Monthly Variation in Lunch Time Calories. International Journal of Population Data Science, 8(3).
• Devine, S., Goulding, J., Skatova, A., & Otto, R. (2023). Decoy Effects in a Massive Real-World Shopping Dataset. International Journal of Population Data Science, 8(3).
• Milligan, G., Bernard, A., Dowthwaite, L., Vallejos, E. P., & Goulding, J. (2023). Generating a Single Session Outcome Measure from Digital Mental Health Platform Footprints Using Natural Language Processing. International Journal of Population Data Science, 8(3).
• Poon, N., Goulding, J., & Skatova, A. (2023). Behavioural entropy as an individual difference. International Journal of Population Data Science, 8(3).
• Sivill, T., Ljevar, V., Goulding, J., & Skatova, A. (2023). What can transactional data reveal about the prevalence of menstrual pain in England?. International Journal of Population Data Science, 8(3).
• Goulding, J., Dolan, E., Long, G., Skatova, A., Harvey, J., Smith, G., & Tata, L. (2023). Forecasting local COVID-19/Respiratory Disease mortality via national longitudinal shopping data: the case for integrating digital footprint data into early warning systems. International Journal of Population Data Science, 8(3).
• Dolan, E., Goulding, J., & Skatova, A. (2023). Data donation of individual shopping data to help predict the occurrence of disease: A pilot study linking individual loyalty card and health survey data to investigate COVID-19. International Journal of Population Data Science, 8(3).
• Mansilla, R., Long, G., Welham, S., Harvey, J., Lukinova, E., Nica-Avram, G., … & Goulding, J. (2023). Identifying and understanding dietary transitions and nutrient deficiency from loyalty card digital footprints. International Journal of Population Data Science, 8(3).
• Parkes, J., Schiazza, G., Martindale, S., Ramchurn, R., Smith, A., & Benford, S. (2023). Digital Footprints in the Video Stream: Survey study of reflections on digital traces of media consumption and potential to use this for insights into well-being. International Journal of Population Data Science, 8(3).
• Seymour, R., Sirl, D., Preston, S., & Goulding, J. (2023, September). Multi-Level Spatial Comparative Judgement Models To Map Deprivation. In Proceedings of the Joint Statistical Meeting 2023.

2022

• Lang, A., Dolan, E., Tata, L., Goulding, J. Qualitative investigation of the novel use of shopping loyalty card data in medical decision making, International Conference on Healthcare Systems, Ergonomics and Patient Safety (HEPS 2022)
• Harvey, J., Hibbert, S., Smith, M., Muthuri, J., Nica-Avram, G., Cultural, Social, and Mapping the landscape of Consumer Food Waste, Appetite, 168 (2022): 105702
• Huntington, Bethany., Goulding, J., Pitchford, N, Pedagogical features of interactive apps for effective learning of foundational skills,  British Journal of Educational Technology
• Mansilla, R., Smith, G., Smith, .A Goulding, Bundle entropy as an optimised measure of consumers’ systematic product choice combinations, Proceedings of IEEE Big Data 2022
• Gavin Long, John Harvey, Gavin Smith, Georgiana Nica-Avram, Gregor Engelmann, James Goulding, Privacy-preserving & machine-learned catchment models for national dietary surveillance via digital footprint data, Proceedings of IEEE Big Data
• Ljevar, V., Avram, G., Harvey, J.,  Branco-Illodo, I, Gallage, S.,  Goulding, J.. Woodall, Smith – Ill-Fated Pro-Social Interactions: Modelling Networked Complaints on a Food Waste Fighting Platform, Proceedings of IEEE Big Data
• Liu, H., Brailsford, T., Goulding, J., Maul, T., Tan, T., & Chaudhuri, D., Towards idea mining: Problem-solution phrases extraction from text, Proceedings of 18th International Conference on Advanced Data Mining and Applications (ADMA) , Lecture Notes in Artificial Intelligence, Springer
• Reedman-Flint, D., Harvey, J., Goulding, J., Gary Priestnall,  I wandered lonely on the cloud: A systematic review of HCI loneliness interventions, International Conference on Computer-Human Interaction Research and Applications 

2021

• Lavelle-Hill, R., Harvey, J., Mazumder, A., Smith. G., Ellis, M., Goulding, J., Using mobile money data and call detail records to explore the risks of urban migration in Tanzania, EPJ Data Science
• Lavelle-Hill, R., Smith, G., Landman, T., Mazumder, A., Goulding, J., Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery, Nature Humanities and Social Science Communications
• Seymour, R., Preston, S. Sirl, D., Goulding, J.,  The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania, Journal of Royal Statistical Society A
• Ljevar, V., Goulding, J., Smith, G., Spence, A. Using Model Class Reliance to Measure Group Effects on Non-Adherence to Asthma Medication, Proceedings of the IEEE Big Data
• Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making, A Smith, J Harvey, J Goulding, G Smith, L Sparks,  Marketing Theory, 2021
• Shiells, K., Dolan, E., Skatova, A., Goulding, J., Public attitudes towards sharing loyalty card data for academic health research: a qualitative study,  BMC Medical Ethics