All Outputs (28)

An empirical critique of the low income low energy efficiency approach to measuring fuel poverty (2024)
Journal Article
Semple, T., Rodrigues, L., Harvey, J., Figueredo, G., Nica-Avram, G., Gillott, M., …Goulding, J. (2024). An empirical critique of the low income low energy efficiency approach to measuring fuel poverty. Energy Policy, 186, Article 114014. https://doi.org/10.1016/j.enpol.2024.114014

Fuel poverty is a complex socioenvironmental issue of increasing global significance. In England, fuel poverty is assessed via the Low Income Low Energy Efficiency (LILEE) indicator, yet concerns exist regarding the efficacy of this metric given its... Read More about An empirical critique of the low income low energy efficiency approach to measuring fuel poverty.

Detecting iodine deficiency risks from dietary transitions using shopping data (2024)
Journal Article
Mansilla, R., Long, G., Welham, S., Harvey, J., Lukinova, E., Nica-Avram, G., …Goulding, J. (2024). Detecting iodine deficiency risks from dietary transitions using shopping data. Scientific Reports, 14(1), Article 1017. https://doi.org/10.1038/s41598-023-50180-7

Plant-based product replacements are gaining popularity. However, the long-term health implications remain poorly understood, and available methods, though accurate, are expensive and burdensome, impeding the study of sufficiently large cohorts. To i... Read More about Detecting iodine deficiency risks from dietary transitions using shopping data.

Assessing relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data (2023)
Conference Proceeding
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 Proceedings: 2023 IEEE International Conference on Big Data: Dec 15 - Dec 18, 2023 Sorrento, Italy. https://doi.org/10.1109/BigData59044.2023.10386740

Life satisfaction significantly contributes to wellbe-ing and is linked to positive outcomes for individual people and society more broadly. However, previous research demonstrates that many factors contribute to the life satisfaction of an individua... Read More about Assessing relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data.

Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake (2023)
Conference Proceeding
Harvey, J., Long, G., Welham, S., Mansilla, R., Rose, P., Thomas, M., …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 Proceedings: 2023 IEEE International Conference on Big Data (BigData) (4530-4538). https://doi.org/10.1109/BigData59044.2023.10386220

Anthocyanins are a class of polyphenols that have received widespread recent attention due to their potential health benefits. However, estimating the dietary intake of anthocyanins at a population level is a challenging task, due to the difficulty o... Read More about Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake.

Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models (2023)
Journal Article
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, Article 7258. https://doi.org/10.1038/s41467-023-42776-4

The COVID-19 pandemic led to unparalleled pressure on healthcare services. Improved healthcare planning in relation to diseases affecting the respiratory system has consequently become a key concern. We investigated the value of integrating sales of... Read More about Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models.

Qualitative Investigation of the Novel Use of Shopping Loyalty Card Data in Medical Decision Making (2023)
Book Chapter
Lang, A., Dolan, E., Tata, L., & Goulding, J. (2023). Qualitative Investigation of the Novel Use of Shopping Loyalty Card Data in Medical Decision Making. In M. Melles, A. Albayrak, & R. H. Goossens (Eds.), Convergence: Breaking Down Barriers Between Disciplines: Proceedings of the International Conference on Healthcare Systems Ergonomics and Patient Safety, HEPS2022. Springer. https://doi.org/10.1007/978-3-031-32198-6_11

This paper describes early results of a small qualitative study investigating the potential impact of shopping loyalty card data (SLCD) in the diagnostic pathway for ovarian cancer. There is early evidence that pharmaceutical products such as pain re... Read More about Qualitative Investigation of the Novel Use of Shopping Loyalty Card Data in Medical Decision Making.

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 (2023)
Journal Article
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), https://doi.org/10.23889/ijpds.v8i3.2273

Introduction & Background Previous studies have found shopping data could increase the predictive accuracy of disease surveillance systems and illuminate behavioural responses in the self-management of symptoms of disease. Yet, accessing individual... Read More about 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.

Using Shopping Data to Improve the Diagnosis of Ovarian Cancer: Computational Analysis of a Web-Based Survey (2023)
Journal Article
Dolan, E., Goulding, J., Tata, L., & Lang, A. (2023). Using Shopping Data to Improve the Diagnosis of Ovarian Cancer: Computational Analysis of a Web-Based Survey. JMIR Cancer, 9, Article e37141. https://doi.org/10.2196/37141

Background Shopping data can be analysed using machine learning techniques to study population health. It is unknown if use of such methods can successfully investigate pre-diagnosis purchases linked to self-medication of symptoms of ovarian cance... Read More about Using Shopping Data to Improve the Diagnosis of Ovarian Cancer: Computational Analysis of a Web-Based Survey.

Pedagogical features of interactive apps for effective learning of foundational skills (2023)
Journal Article
Huntington, B., Goulding, J., & Pitchford, N. J. (2023). Pedagogical features of interactive apps for effective learning of foundational skills. British Journal of Educational Technology, 54(5), 1273-1291. https://doi.org/10.1111/bjet.13317

Interactive apps are commonly used to support the acquisition of foundational skills. Yet little is known about how pedagogical features of such apps affect learning outcomes, attainment and motivation—particularly when deployed in lower‐income conte... Read More about Pedagogical features of interactive apps for effective learning of foundational skills.

Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data (2022)
Conference Proceeding
Mansilla, R., Smith, G., Smith, A., & Goulding, J. (2022). Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data. In Proceedings 2022 IEEE International Conference on Big Data (1044-1053). https://doi.org/10.1109/BigData55660.2022.10021062

Understanding and measuring the predictability of consumer purchasing (basket) behaviour is of significant value. While predictability measures such as entropy have been well studied and leveraged in other sectors, their development and application t... Read More about Bundle entropy as an optimized measure of consumers' systematic product choice combinations in mass transactional data.

Towards Idea Mining: Problem-Solution Phrase Extraction fromText (2022)
Conference Proceeding
Liu, H., Brailsford, T., Goulding, J., Maul, T., Tan, T., & Chaudhuri, D. (2022). Towards Idea Mining: Problem-Solution Phrase Extraction fromText. In Advanced Data Mining and Applications 18th International Conference, ADMA 2022, Brisbane, QLD, Australia, November 28–30, 2022: Proceedings, Part II (3-14). https://doi.org/10.1007/978-3-031-22137-8_1

This paper investigates the feasibility of problem-solution phrases extraction from scientific publications using neural network approaches. Bidirectional Long Short-Term Memory with Conditional Random Fields (Bi-LSTM-CRFs) and Bidirectional Encoder... Read More about Towards Idea Mining: Problem-Solution Phrase Extraction fromText.

Public attitudes towards sharing loyalty card data for academic health research: a qualitative study (2022)
Journal Article
Dolan, E. H., Shiells, K., Goulding, J., & Skatova, A. (2022). Public attitudes towards sharing loyalty card data for academic health research: a qualitative study. BMC Medical Ethics, 23(1), Article 58. https://doi.org/10.1186/s12910-022-00795-8

Background: A growing number of studies show the potential of loyalty card data for use in health research. However , research into public perceptions of using this data is limited. This study aimed to investigate public attitudes towards donating lo... Read More about Public attitudes towards sharing loyalty card data for academic health research: a qualitative study.

Using mobile money data and call detail records to explore the risks of urban migration in Tanzania (2022)
Journal Article
Lavelle-Hill, R., Harvey, J., Smith, G., Mazumder, A., Ellis, M., Mwantimwa, K., & Goulding, J. (2022). Using mobile money data and call detail records to explore the risks of urban migration in Tanzania. EPJ Data Science, 11(8), Article 28. https://doi.org/10.1140/epjds/s13688-022-00340-y

Understanding what factors predict whether an urban migrant will end up in a deprived neighbourhood or not could help prevent the exploitation of vulnerable individuals. This study leveraged pseudonymized mobile money interactions combined with cell... Read More about Using mobile money data and call detail records to explore the risks of urban migration in Tanzania.

Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery (2021)
Journal Article
Lavelle-Hill, R., Smith, G., Mazumder, A., Landman, T., & Goulding, J. (2021). Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery. Humanities and Social Sciences Communications, 8, Article 274. https://doi.org/10.1057/s41599-021-00938-z

Forty million people are estimated to be in some form of modern slavery across the globe. Understanding the factors that make any particular individual or geographical region vulnerable to such abuse is essential for the development of effective inte... Read More about Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery.

Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space (2021)
Journal Article
Boyd, D. S., Perrat, B., Li, X., Jackson, B., Landman, T., Ling, F., …Foody, G. M. (2021). Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space. Humanities and Social Sciences Communications, 8, Article 111. https://doi.org/10.1057/s41599-021-00792-z

This article provides an example of the ways in which remote sensing, Earth observation, and machine learning can be deployed to provide the most up to date quantitative portrait of the South Asian ‘Brick Belt’, with a view to understanding the exten... Read More about Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space.

Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making (2020)
Journal Article
Smith, A., Harvey, J., Goulding, J., Smith, G., & Sparks, L. (2020). Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making. Marketing Theory, 21(1), 53-74. https://doi.org/10.1177/1470593120964947

We develop the concept of exogenous cognition (ExC) as a specific manifestation of an external cognitive system (ECS). Exogenous cognition describes the technological and algorithmic extension of (and annexation of) cognition in a consumption context... Read More about Exogenous cognition and cognitive state theory: The plexus of consumer analytics and decision-making.

Psychological and Demographic Predictors of Plastic Bag Consumption in Transaction Data (2020)
Journal Article
Lavelle-Hill, R., Goulding, J., Smith, G., Clarke, D., & Bibby, P. (2020). Psychological and Demographic Predictors of Plastic Bag Consumption in Transaction Data. Journal of Environmental Psychology, 72, Article 101473. https://doi.org/10.1016/j.jenvp.2020.101473

Despite the success of plastic bag charges in the UK, there are still around a billion single-use plastic bags bought each year in England alone, and the government have made plans to increase the levy from 5 to 10 pence. Previous research has identi... Read More about Psychological and Demographic Predictors of Plastic Bag Consumption in Transaction Data.

FIMS: Identifying, Predicting and Visualising Food Insecurity (2020)
Conference Proceeding
Lucas, B., Smith, A., Smith, G., Perrat, B., Nica-Avram, G., Harvey, J., & Goulding, J. (2020). FIMS: Identifying, Predicting and Visualising Food Insecurity. In WWW '20: Companion Proceedings of the Web Conference 2020 (190-193). https://doi.org/10.1145/3366424.3383538

Food insecurity is a persistent and pernicious problem in the UK. Due to logistical challenges, national food insecurity statistics are unmeasured by government bodies - and this lack of data leads to any local estimates that do exist being routinely... Read More about FIMS: Identifying, Predicting and Visualising Food Insecurity.

Prosocial exchange systems: Nonreciprocal giving, lending, and skill-sharing (2020)
Journal Article
Harvey, J., Smith, A., Golightly, D., Goulding, J., & Gallage, H. S. (2020). Prosocial exchange systems: Nonreciprocal giving, lending, and skill-sharing. Computers in Human Behavior, 107, https://doi.org/10.1016/j.chb.2020.106268

Prosocial exchange systems support cooperation and exchange in support of more sustainable forms of consumption. While often assumed that exchanges within such systems are reciprocal, it remains unproven as to what extent reciprocity occurs. This stu... Read More about Prosocial exchange systems: Nonreciprocal giving, lending, and skill-sharing.

Psychology of personal data donation (2019)
Journal Article
Skatovaid, A., & Goulding, J. (2019). Psychology of personal data donation. PLoS ONE, 14(11), https://doi.org/10.1371/journal.pone.0224240

Advances in digital technology have led to large amounts of personal data being recorded and retained by industry, constituting an invaluable asset to private organizations. The implementation of the General Data Protection Regulation in the EU, incl... Read More about Psychology of personal data donation.