[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122901-en":3,"doc-seo-122901-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},122901,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Comparing Machine Learning Models for YouTube Movie Trailer Comments - An Approach for Accuracy and Overall Sentiment Prediction","This study compares multiple machine learning models to predict the overall sentiment of YouTube comments on movie trailers. A dataset of comments from a well-known trailer is compiled and labeled into positive, negative, and neutral classes using a tokenizer. Models including Naive Bayes, SVM, k-NN, Random Forest, and Bagging are evaluated for accuracy. Results indicate Naive Bayes achieves the highest accuracy and provides the most reliable overall sentiment predictions for comment interpretation.","Comparing Machine Learning Models for YouTube Movie Trailer Comments: An Approach for Accuracy and Overall Sentiment Prediction  \nAryan Nilakhe  \nComputer Science and Engineering, Symbiosis Institute of Technology,  \n Symbiosis International (Deemed University) (SIU), Pune, India  \n[aryan.nilakhe.btech2020@sitpune.edu.in](aryan.nilakhe.btech2020@sitpune.edu.in)  \nAryan Gupta  \nComputer Science and Engineering, Symbiosis Institute of Technology,  \n Symbiosis International (Deemed University) (SIU), Pune, India  \n[aryan.gupta.btech2020@sitpune.edu.in](aryan.gupta.btech2020@sitpune.edu.in)  \nAryan Jadhav  \nComputer Science and Engineering, Symbiosis Institute of Technology,  \n Symbiosis International (Deemed University) (SIU), Pune, India  \n[aryan.jadhav.btech2020@sitpune.edu.in](aryan.jadhav.btech2020@sitpune.edu.in)  \nTanmay Bholane  \nComputer Science and Engineering, Symbiosis Institute of Technology,  \n Symbiosis International (Deemed University) (SIU), Pune, India  \n[tanmay.bholane.btech2020@sitpune.edu.in](tanmay.bholane.btech2020@sitpune.edu.in)  \nRupali Gangarde *  \nComputer Science and Engineering, Symbiosis Institute of Technology,  \n Symbiosis International (Deemed University) (SIU), Pune, India  \n[rupali.gangarde@sitpune.edu.in](rupali.gangarde@sitpune.edu.in)  \nShubhangi Deokar  \nComputer Science and Engineering, Symbiosis Institute of Technology,  \n Symbiosis International (Deemed University) (SIU), Pune, India  \n[shubhangi.deokar@sitpune.edu.in](shubhangi.deokar@sitpune.edu.in)  \nAbstract—This study compares multiple Machine Learning (ML) models for analyzing the sentiment of YouTube comments on movie trailers. The aim of this study is to determine which Machine Learning (ML) model can best accurately predict the overall sentiment of YouTube comments. We compiled a dataset of YouTube comments on a well-known movie trailer and labeled them based on their sentiment using a tokenizer. We then evaluated the performance of different ML models such as Naive Bayes, Support Vector Machine, k-Nearest Neighbors, Random Forest, and Bagging. Our findings show that the Naive Bayes model achieved the highest accuracy for sentiment analysis and provided the most accurate prediction for the overall sentiment of the comments.  \nKeywords-Classification Report ,Sentiment Analysis, Movie Sentiment Prediction, Natural Language Toolkit, Naive Bayes.  \nI. INTRODUCTION  \nSentiment analysis is an application of machine learning that uses Natural Language Processing more commonly known as NLP which includes determining the sentiment of a text. Because of the vast volume of user-generated material, social media platforms have emerged as a major source for sentiment analysis in recent years. As the second most visited websites and the most popular video-sharing platforms, YouTube has a massive number of user comments on its films, including movie trailers. Opinions can be expressed over what are, for example, products, services, individuals, organizations, or an event. [1] The categorization of good and bad content becomes critical for YouTube users to judge how important the video released is  \nbased on user opinion. [2] An example of the relevance of sentiment analysis in this age is the analysis of comments on YouTube about the 2020 US Presidential Election, using SentiWordNet, which revealed a positive reception of Joe Biden's presidency. [3]. In recent literature, various studies have explored sentiment analysis in the context of YouTube videosand user comments, focusing on techniques such as machine learning algorithms for classification [4] . The influence of video duration on user engagement has also been studied, revealing a positive correlation between the amount of negative sentiment in video comments and viewing duration [4] .  \nWe examine the accuracy of multiple machine learning (ML) models for sentiment analysis of YouTube video comments on trailers for movies in this work. The ML models  \nevaluated in this study include [5] Na","cbCaiiW1gWVNpZm6","https://ap.wps.com/l/cbCaiiW1gWVNpZm6","pdf",457215,1,"English","en",105,"# Introduction\n## Problem Statement\n## Objectives\n## Project Purpose","[{\"question\":\"What is the main goal of this study?\",\"answer\":\"The study aims to identify which machine learning model best and most accurately predicts the overall sentiment of YouTube movie-trailer comments.\"},{\"question\":\"How is the dataset of comments prepared for training and testing?\",\"answer\":\"YouTube comments from popular movie trailers are collected and labeled as positive, negative, or neutral using a tokenizer, then used to train and evaluate the models.\"},{\"question\":\"Which machine learning model performs best for sentiment prediction?\",\"answer\":\"Naive Bayes achieves the highest accuracy and gives the most accurate predictions for the overall sentiment of the comments.\"}]","Comparing Machine Learning Models for YouTube Movie Trailer Comments - An Approach for Accuracy and Overall Sentiment Prediction | PDF",1785813571,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"comparing-machine-learning-models-for-youtube-movie-trailer-comments-an-approach-for-accuracy-and-overall-sentiment-prediction","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/comparing-machine-learning-models-for-youtube-movie-trailer-comments-an-approach-for-accuracy-and-overall-sentiment-prediction/122901/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":22,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What is the main goal of this study?","Question",{"text":74,"@type":75},"The study aims to identify which machine learning model best and most accurately predicts the overall sentiment of YouTube movie-trailer comments.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"How is the dataset of comments prepared for training and testing?",{"text":79,"@type":75},"YouTube comments from popular movie trailers are collected and labeled as positive, negative, or neutral using a tokenizer, then used to train and evaluate the models.",{"name":81,"@type":72,"acceptedAnswer":82},"Which machine learning model performs best for sentiment prediction?",{"text":83,"@type":75},"Naive Bayes achieves the highest accuracy and gives the most accurate predictions for the overall sentiment of the comments.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":23},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":28,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":28,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]