WBA-SWPyS

Automatic second-level system for monitoring the population well-being.

Description

The work concerns, as stated in the document drafted for the call, ‘the construction of an automatic second-level system for monitoring the population well-being’. “Second level” because it is based on already built measures, especially by international organisations (such as WHO, OECD, etc.). The system is based on the automation made possible by two robots: the Scraping Robot and the Analytic Robot, which together constitute the body and soul of SWPyS, Scrape the Web. A Python Solution. SWPyS can also be used for other purposes, as outlined in the general description of the study. The aim of the project is to compare indicators of well-being published on different sites, in order to understand how they work and compare them by identifying their merits and shortcomings, in order to:
– Re-engineer the indicators
– Identify the model from which they arise

Result to be enhanced

With this tool, you can answer questions like: “What are the differences between the country systems obtained with apparently equal indicators?” For example, using the OECD betterlifeindex, Norway, Sweden, the Netherlands are in the top three positions, while the same countries are placed respectively at 18th, 19th and 25th position in the WorlData Website for quality of life.

Why is it important?

The project is important because it paves the way for the use of AI techniques applied to the area of people’s health (Wellbeing Indexes). The resulting application makes it possible to analyse similarities and differences between wellbeing indexes. In the resulting frontend (basically a website), some examples are given.