Sentiment Analysis of Data

By: Chauhan, Meetali

A sentiment is known as an attitude or judgment towards any particular event or person. Opinion mining is known as the extraction of these sentiments or opinions from given data. This technique also helps in analysing the kinds of sentiments that people have towards specific objects or services. The best source available to collect the sentiments is the internet. Twitter is known as a social networking platform that users access for posting their views online. Due to the unique properties of Tweets, there is an increase in new challenges. Higher analysis studies are needed in case of sentiments as compared to other domain applications due to their complexities. This research focuses on analysing the sentiments of product reviews for Amazon. Classification as well as feature extraction is applied such that sentiment analysis can be performed. The WDE-LSTM mechanism has been applied for performing sentiment analysis. In addition to this, in this research, the KNN-LSTM mechanism is applied to make certain improvements in the outcomes. Python simulator is used to implement the existing and proposed techniques. Around 94.5% of accuracy is achieved by implementing this improved method.

• Format: Paperback
• Language: English
• ISBN: 6202433760
• ISBN13: 9786202433761
• Release Date: September 2025
• Publisher: LAP Lambert Academic Publishing
• Length: 64 Pages
• Weight: 0.22 lbs.
• Dimensions: 0.1" x 6.0" x 9.0"