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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | A Comparative Analysis of Different Machine Learning Classification Models for Sentiment Analysis |
| Authors Name: | Aryaman Jain , Vanshita Tongia |
| Unique Id: | IJSDR2211044 |
| Published In: | Volume 7 Issue 11, November-2022 |
| Abstract: | With the world transforming into a digital age, the generation of textual documents is increasing at an unprecedented rate. This has consequently given rise to the need to organize these documents into proper categories and structure. Text classification, also known as text categorization, is the process of categorizing text into organized groups. In this paper, IMDB dataset of fifty thousand movie reviews is assessed and a classification system is designed. It compares Linear SVC, Bernoulli Naive Bayes, Logistic Regression, Multinomial Naïve Bayes and Random Forest as classification algorithms for applying sentiment analysis and finding the polarity of the given review. These classifiers were tested, analysed and compared with each other and finally a conclusion was obtained. The authors decided to show the comparison based on several parameters such as precision, accuracy, F1-score, recall and confusion matrix. The classifier which gets the highest among all these parameters is termed as the best machine learning algorithm for the text sentiment analysis of IMDB review data set. |
| Keywords: | Text Classification, Sentiment Analysis, Machine Learning, Logistic Regression, Random Forest, Multinomial Naïve Bayes, Bernoulli’s Naïve Bayes, Linear Support Vector Classifier, Natural language processing |
| Cite Article: | "A Comparative Analysis of Different Machine Learning Classification Models for Sentiment Analysis", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.270 - 277, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211044.pdf |
| Downloads: | 000337074 |
| Publication Details: | Published Paper ID: IJSDR2211044 Registration ID:202494 Published In: Volume 7 Issue 11, November-2022 DOI (Digital Object Identifier): Page No: 270 - 277 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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