Basic tasks of sentiment analysis

TL;DR

This paper discusses fundamental tasks in sentiment analysis, including subjectivity detection and aspect extraction, which are essential for understanding opinions and sentiments in text.

Contribution

It clarifies the basic tasks involved in sentiment analysis, emphasizing the importance of subjectivity detection and aspect extraction for detailed sentiment understanding.

Findings

Subjectivity detection separates objective and subjective sentences.

Aspect extraction identifies opinion targets in text.

These tasks are foundational for advanced sentiment analysis.

Abstract

Subjectivity detection is the task of identifying objective and subjective sentences. Objective sentences are those which do not exhibit any sentiment. So, it is desired for a sentiment analysis engine to find and separate the objective sentences for further analysis, e.g., polarity detection. In subjective sentences, opinions can often be expressed on one or multiple topics. Aspect extraction is a subtask of sentiment analysis that consists in identifying opinion targets in opinionated text, i.e., in detecting the specific aspects of a product or service the opinion holder is either praising or complaining about.