A machine-learning scraping tool for data fusion in the analysis of sentiments about pandemics for supporting business decisions with human-centric AI explanations

Abstract

The COVID-19 pandemic is changing daily routines for many citizens with a high impact on the economy in some sectors. Small-medium enterprises of some sectors need to be aware of both the pandemic evolution and the corresponding sentiments of customers in order to figure out which are the best commercialization techniques. This article proposes an expert system based on the combination of machine learning and sentiment analysis in order to support business decisions with data fusion through web scraping. The system uses human-centric artificial intelligence for automatically generating explanations. The expert system feeds from online content from different sources using a scraping module. It allows users to interact with the expert system providing feedback, and the system uses this feedback to improve its recommendations with supervised learning.