Tools
Tools
Pari, Balaji (2023) Opinion Mining From Book Reviews Using Sentiment Analysis and Topic Modelling. Masters thesis, Dublin, National College of Ireland.
Preview |
PDF (Master of Science)
Download (1MB) | Preview |
Preview |
PDF (Configuration manual)
Download (1MB) | Preview |
Abstract
Books are considered as the bank of knowledge and learning, and they are emerging as an important habit among people. As interest among the people increases, it is important for the author and the publisher to understand the preferences of readers for different genres. A novel approach is introduced to extract the opinions from the reviews provided by the readers using topic modelling. The methodology involves sentiment analysis to predict the rating for each review using classification machine learning algorithms like Decision Tree, Naive Bayes and Random Forest. After rating prediction, reviews are labelled as positive and negative reviews based on the ratings predicted and Topic Modelling is performed using LDA (Latent Dirichlet Allocation) to extract the opinions for positive and negative reviews for different genre so that it helps the authors and publishers to understand about the opinions of readers for different genres. It works as an application framework to know about the opinions of the readers about different genres of books.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Siddig, Abubakr UNSPECIFIED |
| Subjects: | P Language and Literature > PN Literature (General) Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Tamara Malone |
| Date Deposited: | 28 Dec 2024 11:51 |
| Last Modified: | 28 Dec 2024 11:51 |
| URI: | https://norma.ncirl.ie/id/eprint/7245 |
Actions (login required)
 |
View Item |