{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/predicting-the-sentiment-polarity-and-rating","title":"Predicting the Sentiment Polarity and Rating of Yelp Reviews","arxiv_id":"1512.06303","date":"2015-12-20","proceeding":null,"authors":["Andrew Elkouri"],"abstract":"Online reviews of businesses have become increasingly important in recent\nyears, as customers and even competitors use them to judge the quality of a\nbusiness. Yelp is one of the most popular websites for users to write such\nreviews, and it would be useful for them to be able to predict the sentiment or\neven the star rating of a review. In this paper, we develop two classifiers to\nperform positive/negative classification and 5-star classification. We use\nNaive Bayes, Support Vector Machines, and Logistic Regression as models, and\nachieved the best accuracy with Logistic Regression: 92.90% for\npositive/negative classification, and 63.92% for 5-star classification. These\nresults demonstrate the quality of the Logistic Regression model using only the\ntext of the review, yet there is a promising opportunity for improvement with\nmore data, more features, and perhaps different models.","url_abs":"http://arxiv.org/abs/1512.06303v1","url_pdf":"http://arxiv.org/pdf/1512.06303v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"predicting-the-sentiment-polarity-and-rating","repo_url":"https://github.com/cyn228/Yelp-Sentiment","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"predicting-the-sentiment-polarity-and-rating","repo_url":"https://github.com/hwang787/Yelp-Sentiment","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}