Leveraging Sentiment Analysis for Enhanced Educational Video Recommendations on YouTube-Easyfy
摘要
The difficulty of sifting through the multitude of internet resources is addressed by Easyfy, a software program created to streamline the learning process. Easyfy seeks to help students find the best resources in the age of readily available internet content by applying a set of rules or criteria. Since popularity or view count by themselves may not always imply the quality of instructional content, Easyfy’s main focus is on YouTube resources. Easyfy, on the other hand, takes a novel tack by scrutinizing user commentary on YouTube videos. Easyfy distinguishes between good and negative feedback by analyzing and interpreting the comments to determine the sentiment conveyed. Sentiment analysis of YouTube comments is essential for gauging a video’s overall popularity. Easyfy helps people comprehend the ratio of positive to negative sentiment by measuring the sentiment of comments. This insightful information can help students make well-informed decisions about the suitability and connection of a certain video to their learning goals. Sentiment analysis in YouTube comments is used for purposes other than personal preference. Easyfy uses this data to suggest the "best" video for a particular subject. The program analyzes the tone of comments in addition to popularity measures to identify which video is most likely to offer the most thorough and well-received information on a certain topic.