[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125826-en":3,"doc-seo-125826-105":30,"detail-sidebar-cat-0-en-105":91},{"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":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125826,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Review and Analysis of Product Review Sentiment Analysis using Improved Machine Learning Techniques","Sentiment analysis serves as a key big-data and social-media task by transforming opinions in product reviews into actionable signals. The research introduces a simulation-based design and evaluation of product review sentiment analysis using improved machine learning techniques, aiming to build a robust model with higher accuracy and efficiency than existing methods. The work reviews prior literature, details an enhanced methodology with feature extraction, sentiment classification, and model optimization, and assesses performance using accuracy, precision, recall, and F1-score versus baseline and state-of-the-art systems.","Review and Analysis of Product Review Sentiment Analysis using Improved Machine Learning  \nTechniques  \nPawan Kumar1, Dr. Mukesh Kumar2  \n1Research Scholar, Department ofCSE, Rabindra Nath Tagore University, Bhopal, India 2Associate Professor, Department ofCSE, Rabindra Nath Tagore University, Bhopal, India  \nAbstract— : Sentiment analysis has emerged as a crucial task in the era of big data and social media. Understanding the sentiments expressed in product reviews is vital for businesses to gauge customer satisfaction and make informed decisions. This research paper presentsa design simulation and assessment of product review sentiment analysis using improved machine learning techniques. The aim is to develop a robust sentiment analysis model that outperforms existing approaches in accuracy and efficiency. We propose a novel methodology that combines advanced feature extraction, sentiment classification algorithms, and model optimization techniques.The introduction provides an overview of the importance of sentiment analysis in the context of product reviews and the challenges faced by conventional methods. It also outlines the objectives and scope of this research. The related works section presents a comprehensive review of existing literature and highlights the limitations of current approaches. The proposed methodology section describes the technical details of our enhanced machine learning approach and the reasoning behind the selected techniques.In the analysis of sample results, we evaluate the performance of our proposed model on a diverse dataset of product reviews. We present the accuracy, precision, recall, and F1-score metrics, along with a comparison to baseline models and state-of-the-art sentiment analysis systems. Furthermore, we discuss the model's robustness in handling various types of products and reviews.  \nOur research demonstrates significant improvements in sentiment analysis accuracy compared to traditional methods. We introduce tablesand graphs to illustrate the model's performance in different scenarios and identify its strengths and weaknesses. The paper concludes by discussing the implications of our findings, potential applications in industry, and directions for future research. Overall, this research contributes to the advancement of sentiment analysis techniques and provides a valuable resource for businesses aiming to enhance their understanding of customer sentiments through product reviews...  \nKeywords- Product Review, Sentiment Analysis, Tweets, Machine Learning, Natural Language Processing, Deep Learning, Ensemble Learning  \nI. INTRODUCTION  \nIn the digital age of information and connectivity, the internet has revolutionized the way people interact, communicate, and make purchasing decisions. With the advent of e-commerce platforms, social media networks, and online forums, consumers now have unprecedented avenues to express their opinions and experiences about products and services they encounter. Product reviews have become a potent source of information for potential buyers, guiding their decisions and influencing their perceptions of a brand or product. Consequently, businesses have recognized the significance of monitoring and understanding these user-generated sentiments to adapt their strategies, enhance customer satisfaction, and maintain a competitive edge in the market.  \nSentiment analysis, also known as opinion mining, is a natural language processing (NLP) technique that automates the process of determining the sentiment expressed in a piece of text, be it positive, negative, or neutral. In the context of product reviews, sentiment analysis plays a pivotal role in extracting valuable insights from vast amounts of unstructured textual data. By discerning the overall sentiment towards a product or its specific attributes, businesses can gauge customer satisfaction, identify pain points, detect emerging trends, and make datadriven decisions to improve their products and servic","cbCail2Uv6jmcdV0","https://ap.wps.com/l/cbCail2Uv6jmcdV0","pdf",164063,1,6,"English","en",105,"# Introduction\n## Sentiment analysis background and importance\n## Limitations of conventional approaches\n## Machine learning and deep learning directions\n# Related Works\n# Proposed Methodology\n# Analysis and Results\n## Evaluation metrics and comparisons\n## Robustness across product types\n# Conclusion","[{\"question\":\"What problem does the paper address and why is it important?\",\"answer\":\"The paper addresses sentiment analysis for product reviews to extract customer satisfaction insights. It helps businesses monitor opinions, understand trends, and make data-driven decisions.\"},{\"question\":\"How does the proposed approach aim to improve sentiment analysis?\",\"answer\":\"It proposes an improved machine learning methodology that combines advanced feature extraction, sentiment classification algorithms, and model optimization.\"},{\"question\":\"What metrics are used to evaluate the model’s performance?\",\"answer\":\"The paper evaluates accuracy, precision, recall, and F1-score, and compares results against baseline and state-of-the-art sentiment analysis systems.\"}]","Review and Analysis of Product Review Sentiment Analysis using Improved Machine Learning Techniques | PDF",1785901430,15,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"review-and-analysis-of-product-review-sentiment-analysis-using-improved-machine-learning-techniques","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/review-and-analysis-of-product-review-sentiment-analysis-using-improved-machine-learning-techniques/125826/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the paper address and why is it important?","Question",{"text":75,"@type":76},"The paper addresses sentiment analysis for product reviews to extract customer satisfaction insights. It helps businesses monitor opinions, understand trends, and make data-driven decisions.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the proposed approach aim to improve sentiment analysis?",{"text":80,"@type":76},"It proposes an improved machine learning methodology that combines advanced feature extraction, sentiment classification algorithms, and model optimization.",{"name":82,"@type":73,"acceptedAnswer":83},"What metrics are used to evaluate the model’s performance?",{"text":84,"@type":76},"The paper evaluates accuracy, precision, recall, and F1-score, and compares results against baseline and state-of-the-art sentiment analysis systems.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]