All Outputs (37)

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.

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)
Conference Proceeding
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.

Seasonal Variation in Collective Mood via Twitter Content and Medical Purchases (2017)
Conference Proceeding
Dzogang, F., Goulding, J., Lightman, S., & Cristianini, N. (2017). Seasonal Variation in Collective Mood via Twitter Content and Medical Purchases. In Advances in Intelligent Data Analysis XVI (63-74). https://doi.org/10.1007/978-3-319-68765-0_6

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)
Conference Proceeding
Priestnall, G., Goulding, J., Smith, A., & Arss, N. (2017). Exploring the capabilities of Projection Augmented Relief Models (PARM).

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)
Conference Proceeding
Goulding, J., Preston, S. P., & Smith, G. (2016). Event series prediction via non-homogeneous Poisson process modelling. In 2016 IEEE 16th International Conference on Data Mining (ICDM). https://doi.org/10.1109/ICDM.2016.0027

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)
Conference Proceeding
Alanazi, S., Goulding, J., & McAuley, D. (2016). Cross-system Recommendation: User-modelling via Social Media versus Self-Declared Preferences. In HT '16: Proceedings of the 27th ACM Conference on Hypertext and Social Media (183-188). https://doi.org/10.1145/2914586.2914640

© 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)
Conference Proceeding
Smith, G., & Goulding, J. (2015). A novel symbolization technique for time-series outlier detection. In 2015 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/BigData.2015.7364037

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, doi:10.1007/978-3-319-23525-7_33

AMP: a new time-frequency feature extraction method for intermittent time-series data (2015)
Conference Proceeding
Barrack, D. S., Goulding, J., Hopcraft, K., Preston, S., & Smith, G. (2015). AMP: a new time-frequency feature extraction method for intermittent time-series data.

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.

A refined limit on the predictability of human mobility (2014)
Conference Proceeding
Smith, G., Wieser, R., Goulding, J., & Barrack, D. (2014). A refined limit on the predictability of human mobility. In 2014 IEEE International Conference on Pervasive Computing and Communications (PerCom). https://doi.org/10.1109/PerCom.2014.6813948

It has been recently claimed that human movement is highly predictable. While an upper bound of 93% predictability was shown, this was based upon human movement trajectories of very high spatiotemporal granularity. Recent studies reduced this spatiot... Read More about A refined limit on the predictability of human mobility.

A data driven approach to mapping urban neighbourhoods (2014)
Conference Proceeding
Brindley, P., Goulding, J., & Wilson, M. L. (2014). A data driven approach to mapping urban neighbourhoods.

Neighbourhoods have been described by the UK Secretary of State for Communities and Local Government as the “building blocks of public service society”. Despite this, difficulties in data collection combined with the concept’s subjective nature have... Read More about A data driven approach to mapping urban neighbourhoods.

Towards optimal symbolization for time series comparisons (2013)
Conference Proceeding
Smith, G., Goulding, J., & Barrack, D. (2013). Towards optimal symbolization for time series comparisons. In 2013 IEEE 13th International Conference on Data Mining Workshops. https://doi.org/10.1109/ICDMW.2013.59

The abundance and value of mining large time series data sets has long been acknowledged. Ubiquitous in fields ranging from astronomy, biology and web science the size and number of these datasets continues to increase, a situation exacerbated by the... Read More about Towards optimal symbolization for time series comparisons.