2019
DOI: 10.5120/ijca2019919675
|View full text |Cite
|
Sign up to set email alerts
|

Using BERT for Checking the Polarity of Movie Reviews

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
3
1
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(1 citation statement)
references
References 20 publications
0
1
0
Order By: Relevance
“…Recently, research interest has increased significantly in sentiment analysis using new methods and algorithms based on deep learning, machine learning, and the use of transformers. Many algorithms, such as Naive Bayes, Decision Tree, KNN, SVM, and LSTM, as well as transformer-based algorithms, were applied to the IMDb dataset, which is a balanced sentiment dataset [7], [8], [9]. For various sentiment classification approaches, Prajval et al [10] provide a comparative study, and the technical and non-technical aspects and challenges of opinion mining and sentiment analysis are discussed in [11].…”
Section: Introductionmentioning
confidence: 99%
“…Recently, research interest has increased significantly in sentiment analysis using new methods and algorithms based on deep learning, machine learning, and the use of transformers. Many algorithms, such as Naive Bayes, Decision Tree, KNN, SVM, and LSTM, as well as transformer-based algorithms, were applied to the IMDb dataset, which is a balanced sentiment dataset [7], [8], [9]. For various sentiment classification approaches, Prajval et al [10] provide a comparative study, and the technical and non-technical aspects and challenges of opinion mining and sentiment analysis are discussed in [11].…”
Section: Introductionmentioning
confidence: 99%