Two-dimensional Sentiment Analysis of text

TL;DR

This paper introduces a novel two-dimensional sentiment analysis method that classifies text based on emotional space using lexical features and supervised learning.

Contribution

It proposes a new two-dimensional sentiment classification approach leveraging lexical resources and supervised learning, enhancing emotional understanding in text analysis.

Findings

Effective classification of text in emotional space

Utilizes lexical resources for feature extraction

Employs supervised learning for training

Abstract

Sentiment Analysis aims to get the underlying viewpoint of the text, which could be anything that holds a subjective opinion, such as an online review, Movie rating, Comments on Blog posts etc. This paper presents a novel approach that classify text in two-dimensional Emotional space, based on the sentiments of the author. The approach uses existing lexical resources to extract feature set, which is trained using Supervised Learning techniques.