All Outputs (43)

The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania (2022)
Journal Article
Seymour, R. G., Sirl, D., Preston, S. P., Dryden, I. L., Ellis, M. J., Perrat, B., & Goulding, J. (2022). The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania. Journal of the Royal Statistical Society: Series C, 71(2), 288-308. https://doi.org/10.1111/rssc.12532

Identifying the most deprived regions of any country or city is key if policy makers are to design successful interventions. However, locating areas with the greatest need is often surprisingly challenging in developing countries. Due to the logistic... Read More about The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling 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., Bales, K., Choi-Fitzpatrick, A., Goulding, J., Marsh, S., & 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.

Model Class Reliance for Random Forests (2020)
Presentation / Conference Contribution
Smith, G., Mansilla Lobos, R., & Goulding, J. (2020, December). Model Class Reliance for Random Forests. Presented at 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada

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.

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)
Presentation / Conference Contribution
Lucas, B., Smith, A., Smith, G., Perrat, B., Nica-Avram, G., Harvey, J., & Goulding, J. (2020, April). FIMS: Identifying, Predicting and Visualising Food Insecurity. Presented at The Web Conference 2020 - Companion of the World Wide Web Conference, WWW 2020, Taipei Taiwan

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, 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, December). The unbanked and poverty: predicting area-level socio-economic vulnerability from M-Money transactions. Presented at 2018 IEEE international Conference on Big Data, Seattle, USA

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.

Seasonal Variation in Collective Mood via Twitter Content and Medical Purchases (2017)
Presentation / Conference Contribution
Dzogang, F., Goulding, J., Lightman, S., & Cristianini, N. (2017, October). Seasonal Variation in Collective Mood via Twitter Content and Medical Purchases. Presented at 16th International Symposium, IDA 2017, London, UK

The analysis of sentiment contained in vast amounts of Twitter messages has reliably shown seasonal patterns of variation in multiple studies, a finding that can have great importance in the understanding of seasonal affective disorders, particularly... Read More about Seasonal Variation in Collective Mood via Twitter Content and Medical Purchases.

Exploring the capabilities of Projection Augmented Relief Models (PARM) (2017)
Presentation / Conference Contribution
Priestnall, G., Goulding, J., Smith, A., & Arss, N. (2017, April). Exploring the capabilities of Projection Augmented Relief Models (PARM). Presented at Geographical Information Science Research UK Conference 2017, Manchester, UK

This paper explores the broad capabilities of physical landscape models when augmented by projection, termed Projection Augmented Relief Models (PARM). This includes experiences of developing PARM displays in public settings such as museums and visit... Read More about Exploring the capabilities of Projection Augmented Relief Models (PARM).

Event series prediction via non-homogeneous Poisson process modelling (2016)
Presentation / Conference Contribution
Goulding, J., Preston, S. P., & Smith, G. (2016, December). Event series prediction via non-homogeneous Poisson process modelling. Presented at 2016 IEEE International Conference on Data Mining (ICDM), Barcelona, Spain

Data streams whose events occur at random arrival times rather than at the regular, tick-tock intervals of traditional time series are increasingly prevalent. Event series are continuous, irregular and often highly sparse, differing greatly in nature... Read More about Event series prediction via non-homogeneous Poisson process modelling.

Cross-system Recommendation: User-modelling via Social Media versus Self-Declared Preferences (2016)
Presentation / Conference Contribution
Alanazi, S., Goulding, J., & McAuley, D. (2016, July). Cross-system Recommendation: User-modelling via Social Media versus Self-Declared Preferences. Presented at HT '16: 27th ACM Conference on Hypertext and Social Media, Halifax, Nova Scotia, Canada

© 2016 ACM. It is increasingly rare to encounter aWeb service that doesn't engage in some form of automated recommendation, with Collaborative Filtering (CF) techniques being virtually ubiquitous as the means for delivering relevant content. Yet seve... Read More about Cross-system Recommendation: User-modelling via Social Media versus Self-Declared Preferences.

A novel symbolization technique for time-series outlier detection (2015)
Presentation / Conference Contribution
Smith, G., & Goulding, J. A novel symbolization technique for time-series outlier detection. Presented at 2015 IEEE International Conference on Big Data

The detection of outliers in time series data is a core component of many data-mining applications and broadly applied in industrial applications. In large data sets algorithms that are efficient in both time and space are required. One area where sp... Read More about A novel symbolization technique for time-series outlier detection.

Towards computation of novel ideas from corpora of scientific text (2015)
Journal Article
Liu, H., Goulding, J., & Brailsford, T. (2015). Towards computation of novel ideas from corpora of scientific text. Lecture Notes in Artificial Intelligence, 9285, https://doi.org/10.1007/978-3-319-23525-7_33

AMP: a new time-frequency feature extraction method for intermittent time-series data (2015)
Presentation / Conference Contribution
Barrack, D. S., Goulding, J., Hopcraft, K., Preston, S., & Smith, G. AMP: a new time-frequency feature extraction method for intermittent time-series data. Presented at 1st International Workshop on Mining and Learning from Time Series (MiLeTS)

The characterisation of time-series data via their most salient features is extremely important in a range of machine learning task, not least of all with regards to classification and clustering. While there exist many feature extraction techniques... Read More about AMP: a new time-frequency feature extraction method for intermittent time-series data.