Open AccessSentiment Analysis Based on Movie Reviews using Various Classification Techniques : A Review
Author(s) -
Karishma S. Kaushik,
Mahesh Parmar
Publication year - 2021
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit217329
Subject(s) - sentiment analysis , computer science , feeling , sadness , support vector machine , artificial intelligence , happiness , natural language processing , perception , machine learning , psychology , anger , social psychology , neuroscience
Sentimental analysis is also called "opinion mining" analyses attitudes and classifies text views. It relates to the use of natural language processing, text, and linguistic processing. A huge amount of data is created with the rapid growth of web technologies. Social networking sites are now popular and normal places where feelings can be shared by short messages. These sentiments involve happiness, sadness, anxiety, fear, etc. The analysis of short texts tends to recognize the crowd's sentiment. Sentiment Analysis on IMDb moviereviews describes a reviewer's general feeling or impression of a movie. Since the perceptions of humans improve the effectiveness of products & since a movie'ssuccess or failure depending on its review, costs are rising, and a good sentiment analysis model needs to be developed, that classifies moviereviews. Machine learning methods use ML algorithms to carry out sentiment analysis as a standard classification problem using syntactic and language characteristics. There are some methods of machine learning used for sentiment analysis in this paper. Most of the sentiment analysis is performed using SVM, RF, ANN, and NB, Algorithms of DT, BN, & KNN.