Multi-Dimensional Aspect Analysis of Text Input through Human Emotion and Social Factors

Abstract

Sentiment Analysis is one of the research fields of computer science that analyzes human feedback and response based on text inputs. So far there has been a significant number of works on sentiment analysis of recorded text inputs. In this paper, we are proposing a multi-dimensional aspect-based sentiment analysis. This analysis will represent the influence of human emotion and social factors on the response of individuals in different events. The social media platforms have already proved that people's opinion varies to a large extent on any given topic. We want to present a data-analyzed visualization of this common scenario and find out the causes behind. The primary result of the experiment of this hypothesis points out the significant influence of human factors on the response of an individual to some common scenario. The next steps of this research will include larger user study data collection and find out the most intriguing key factors. Thus in this multi-dimensional aspect-based sentiment analysis, where we are finding out the background story of text input in addition to its polarity detection.