All Outputs (30)

Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset (2024)
Journal Article
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), Article 62. https://doi.org/10.3390/soc14050062

The new Domestic Workers Dataset is the largest single set of surveys (n = 11,759) of domestic workers to date. Our analysis of this dataset reveals features about the lives and work of this “hard-to-find” population in India—a country estimated to h... Read More about Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset.

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)
Presentation / Conference Contribution
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.

Expert perspectives on how educational technology may support autonomous learning for remote out-of-school children in low-income contexts (2023)
Journal Article
Huntington, B., Goulding, J., & Pitchford, N. J. (2023). Expert perspectives on how educational technology may support autonomous learning for remote out-of-school children in low-income contexts. International Journal of Educational Research Open, 5, Article 100263. https://doi.org/10.1016/j.ijedro.2023.100263

Across Sub-Saharan African, 98 million children are illiterate and innumerate and do not attend school. Educational technologies (EdTech) that promote autonomous learning may ameliorate this learning poverty. Yet, little is known if or how these tech... Read More about Expert perspectives on how educational technology may support autonomous learning for remote out-of-school children in low-income contexts.

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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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.

Model Class Reliance for Random Forests (2020)
Presentation / Conference Contribution
Smith, G., Mansilla Lobos, R., & Goulding, J. (2020). Model Class Reliance for Random Forests. In Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020)

Variable Importance (VI) has traditionally been cast as the process of estimating each variable's contribution to a predictive model's overall performance. Analysis of a single model instance, however, guarantees no insight into a variables relevance... Read More about Model Class Reliance for Random Forests.

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.

Identifying food insecurity in food sharing networks via machine learning (2020)
Journal Article
Nica-Avram, G., Harvey, J., Smith, G., Smith, A., & Goulding, J. (2021). Identifying food insecurity in food sharing networks via machine learning. Journal of Business Research, 131, 469-484. https://doi.org/10.1016/j.jbusres.2020.09.028

© 2020 Elsevier Inc. Food insecurity in the UK has captured public attention. However, estimates of its prevalence are deeply contentious. The lack of precision on the volume of emergency food assistance currently provided to those in need is made ev... Read More about Identifying food insecurity in food sharing networks via machine learning.

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, Article 106268. 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), Article e0224240. 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.

Food sharing, redistribution, and waste reduction via mobile applications: a social network analysis (2019)
Journal Article
Harvey, J., Smith, A., Goulding, J., & Branco-illodo, I. (2020). Food sharing, redistribution, and waste reduction via mobile applications: a social network analysis. Industrial Marketing Management, 88, 437-448. https://doi.org/10.1016/j.indmarman.2019.02.019

Food sharing mobile applications are becoming increasingly popular, but little is known about the new social configurations of people using them, particularly those applications that use consumers as voluntary intermediaries in supply chains. This ar... Read More about Food sharing, redistribution, and waste reduction via mobile applications: a social network analysis.

The unbanked and poverty: predicting area-level socio-economic vulnerability from M-Money transactions (2018)
Presentation / Conference Contribution
Engelmann, G., Smith, G., & Goulding, J. (2018). The unbanked and poverty: predicting area-level socio-economic vulnerability from M-Money transactions.

Emerging economies around the world are often characterized by governments and institutions struggling to keep key demographic data streams up to date. A demographic of interest particularly linked to social vulnerability is that of poverty and socio... Read More about The unbanked and poverty: predicting area-level socio-economic vulnerability from M-Money transactions.

Generating vague neighbourhoods through data mining of passive web data (2017)
Journal Article
Brindley, P., Goulding, J., & Wilson, M. L. (in press). Generating vague neighbourhoods through data mining of passive web data. International Journal of Geographical Information Science, 32(3), https://doi.org/10.1080/13658816.2017.1400549

Neighbourhoods have been described as \the building blocks of public services society". Their subjective nature, however, and the resulting difficulties in collecting data, means that in many countries there are no officially defined neighbourhoods e... Read More about Generating vague neighbourhoods through data mining of passive web data.