{"repo":"ntthanh2603/segmentation-analysis","free":true,"listed":false,"github":"https://github.com/ntthanh2603/segmentation-analysis","clone":"git clone https://github.com/ntthanh2603/segmentation-analysis.git","description":"🌟 Project segmantation analysis 🌟","language":"Python","stars":23,"topics":["analysis","analytics","birnn","jupyter-notebook","pyautogui","python","selenium","training","transformer"],"license":null,"category":"scrapers-browser-automation","readme_excerpt":"Project segmentation-analysis Sentiment classification of comments provides better understanding of audience reception, supporting filmmakers, streaming platforms, and marketers in making decisions (cutting, adding showtimes, implementing opportunities or campaigns quickly, staying ahead of trends). Sentiment classification faces several challenges: film review language is highly metaphorical, unclear context, etc. Due to the issues mentioned above, accurate classification requires applying good Natural Language Processing (NLP) techniques to capture more subtle language nuances. In this report, we conducted analysis and comparison of two modern deep learning models: Transformer (PhoBERT, DistilBERT) and Bi-RNN (with LSTM layers) for sentiment analysis based on Vietnamese movie reviews. Team Members: - Nguyen Tuan Thanh - 22022624 - Vu Dinh Tho - 22022580 - Dinh Van Sinh - 22022615 - Nguyen Manh Hung - 22022623 - Nguyen Cong Thanh - 22022630 Objectives: - Build and deploy models: Develop two deep learning models - Transformer and Bi-RNN for sentiment analysis. - Evaluate and compare: Compare the performance of both models through metrics such as Accuracy, F1-Score, Precision, and Recall. - Practical applications: Apply analysis results to fields such as customer feedback management, product review monitoring, or social media sentiment surveillance. Data: Comments from Facebook posts collected using Selenium and PyAutoGUI libraries. Using Pandas and supporting libraries like e","default_branch":null,"files":null,"tree":[],"storefront":"/r/ntthanh2603","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ntthanh2603/segmentation-analysis/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}