A Comparative Sentiment Analysis of Digital and Robot Pet Companions in Various Locations

Abstract

This study is to find out whether geographic locations have an impact on emotion towards robotic and digital pet companions, using machine learning models and hypothesis testing. This investigation will show and assess different machine learning models for sentiment analysis on labeled datasets and pick the model with the best performance. This exploration will collect unlabeled data about digital robot companions from various regions, pre-process the information, and apply a chosen machine learning model to figure out sentiments in the unlabeled dataset. Then use chi-square to evaluate the connection between area and sentiment towards robot companions and find out whether there is a critical distinction in the sentiment between various locations. There will be discussion about the result, limitations, and its suggestions for understanding human-machine relationships in various zones. The investigation will give potential results for future research.