All Outputs (6)

Predicting Healthy Start Scheme Uptake using Deprivation and Food Insecurity Measures (2024)
Presentation / Conference Contribution
Makokoro, K., Long, G., Harvey, J., Smith, A., Welham, S., Mansilla, R., Lukinova, E., & Goulding, J. (2024, May). Predicting Healthy Start Scheme Uptake using Deprivation and Food Insecurity Measures. Presented at 2nd Digital Footprints Conference: Linking Digital Data for Social Impact, Bristol, UK

Utilising User Data from a Food-Sharing App to Evidence the "Heat-or-Eat" Dilemma (2024)
Presentation / Conference Contribution
Semple, T., Harvey, J., Rodrigues, L., Gillott, M., Figueredo, G., & Nica-Avram, G. (2024, May). Utilising User Data from a Food-Sharing App to Evidence the "Heat-or-Eat" Dilemma. Presented at 2nd Digital Footprints Conference: Linking Digital Data for Social Impact, Bristol, UK

Introduction & Background
Previous literature has found that financially vulnerable households often make involuntary spending trade-offs between necessities, particularly energy and food. This effect is especially pronounced during winter, when hom... Read More about Utilising User Data from a Food-Sharing App to Evidence the "Heat-or-Eat" Dilemma.

Foodinsecurity.london: Developing a food-insecurity prevalence map for London - a machine learning from food-sharing footprints (2024)
Presentation / Conference Contribution
Milligan, G., Nica-Avram, G., Harvey, J., & Goulding, J. (2024, May). Foodinsecurity.london: Developing a food-insecurity prevalence map for London - a machine learning from food-sharing footprints. Presented at 2nd Digital Footprints Conference: Linking Digital Data for Social Impact, Bristol, UK

Introduction & Background
The ability of policymakers to positively transform food environments requires robust empirical evidence that can inform decisions. At present, there is limited data on food-insecurity in the UK that can be used to inform i... Read More about Foodinsecurity.london: Developing a food-insecurity prevalence map for London - a machine learning from food-sharing footprints.

Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake (2023)
Presentation / Conference Contribution
Harvey, J., Long, G., Welham, S., Mansilla, R., Rose, P., Thomas, M., Milligan, G., Dolan, E., Parkes, J., Makokoro, K., & Goulding, J. (2023, December). Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake. Presented at 2023 IEEE International Conference on Big Data (BigData), Sorrento, Itlay

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 relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data (2023)
Presentation / Conference Contribution
Milligan, G., Harvey, J., Dowthwaite, L., Vallejos, E. P., Nica-Avram, G., & Goulding, J. (2023, December). Assessing relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data. Presented at 2023 IEEE International Conference on Big Data, Sorrento, Italy

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.

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.