Method comparison of Naïve Bayes, Logistic Regression, and SVM for Analyzing Movie Reviews Article Swipe
Muhammad Maulidan Aziz
,
Mahendra Dwifebri Purbalaksono
,
Adiwijaya Adiwijaya
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.47065/bits.v4i4.2644
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.47065/bits.v4i4.2644
A film can be categorized as a successful film based on the reviews given by the critics. The reviews can range from professional critics to public reviews from the general audience. Due to a large number of reviews and opinions on a film, this study aims to create a sentiment analysis model and compare the methods used to analyze datasets from a movie review. Sentiment Analysis is a method for studying and analyzing opinions, then classifying these opinions into several classes. This research will use the Naïve Bayes method, Logistic Regression, and Support Vector Machine (SVM) to analyze film review data. The film review dataset used is a collection of film reviews taken from the Rotten Tomatoes website and will be pre-processed before implementing the Naïve Bayes, Logistic Regression, and SVM methods. The SVM classifier with 80:20 data splitting has the best performance, with a result of 99.4% accuracy score and 93.5% F1 score.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.47065/bits.v4i4.2644
- https://ejurnal.seminar-id.com/index.php/bits/article/download/2644/1876
- OA Status
- diamond
- Cited By
- 6
- References
- 21
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4366586162
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4366586162Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.47065/bits.v4i4.2644Digital Object Identifier
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Method comparison of Naïve Bayes, Logistic Regression, and SVM for Analyzing Movie ReviewsWork title
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articleOpenAlex work type
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enPrimary language
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2023Year of publication
- Publication date
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2023-03-29Full publication date if available
- Authors
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Muhammad Maulidan Aziz, Mahendra Dwifebri Purbalaksono, Adiwijaya AdiwijayaList of authors in order
- Landing page
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https://doi.org/10.47065/bits.v4i4.2644Publisher landing page
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https://ejurnal.seminar-id.com/index.php/bits/article/download/2644/1876Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://ejurnal.seminar-id.com/index.php/bits/article/download/2644/1876Direct OA link when available
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Support vector machine, Logistic regression, Naive Bayes classifier, Artificial intelligence, Machine learning, Computer science, Bayes' theorem, Classifier (UML), Data mining, Bayesian probabilityTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
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2024: 6Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5040147499, https://openalex.org/A5061473902, https://openalex.org/A5090937388 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I862893732 |
| citation_normalized_percentile.value | 0.92215279 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |