The procedure of automatic sentiment analysis is more or less the same as the rule-based approach. It just uses more advanced algorithms to explore deeper layers of the sentiments of a text. 3.

This paper describes a rule-based sentiment analysis algorithm for polarity classification of financial news articles. The system utilizes a prior polarity lexicon to classify the financial news ...

The paper considers the analysis of the subjective information from user-generated content. The purpose of this research is to develop a rule-based classifier for the sentiment analysis within the ...

Rule-based methods use pre-defined rules and lexicons to determine the sentiment of a text, while machine learning-based methods use algorithms to learn from data and identify patterns in the text.

The Yelp Dataset comprises data collected from 8,021,122 reviews and 209,393 businesses located in 10 major metropolitan areas. This comprehensive dataset includes multiple aspects related to the ...

Today, a plethora of algorithm-based digital applications and analysis tools are being used to gather data about the customer experience in order to enhance it.

Sentiment Analysis uses natural language processing (see Google Wave), computational linguistics and text mining to identify the attitudes among writer(s)/speaker(s) on a particular topic. Expand ...