Identifying food insecurity in food sharing networks via machine learning
نویسندگان
چکیده
Food insecurity in the UK has captured public attention. However, estimates of its prevalence are deeply contentious. The lack precision on volume emergency food assistance currently provided to those need is made even more ambiguous due increasing use peer-to-peer sharing systems (e.g. OLIO). While these initiatives exist as a solution waste rather than poverty, they nonetheless carrying hidden share burden, with socio-economic status technology-assisted donors, volunteers, and recipients remaining obscure. In this article we examine relationship between deprivation generally, before applying machine learning techniques develop predictive model based upon aggregated behaviours by OLIO users UK. We demonstrate that data from can help quantify previously aspect make case for reformed approach modelling insecurity.
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ژورنال
عنوان ژورنال: Journal of Business Research
سال: 2021
ISSN: ['1873-7978', '0148-2963']
DOI: https://doi.org/10.1016/j.jbusres.2020.09.028