论文标题
YouTube广告视图情感分析使用深度学习和机器学习
YouTube Ad View Sentiment Analysis using Deep Learning and Machine Learning
论文作者
论文摘要
情感分析目前是研究的重要领域。随着互联网使用的进步，社交媒体，网站，博客，观点，评级等的创建迅速增加。人们以喜欢，不喜欢，评论等形式的社交媒体帖子表达自己的反馈和情感。观众生成或用户生成的数据或YouTube上的内容的快速增长导致YouTube情感分析的增加。因此，分析公共反应已成为技术领域中信息提取和数据可视化的必不可少的需求。这项研究可以使用深度学习和机器学习算法（例如线性回归（LR），支持向量机（SVM），决策树（DT），随机森林（RF）和人工神经网络（ANN）（ANN）等深度学习和机器学习算法预测YouTube AD视图情感。最后，基于从不同模型中获得的实验结果进行比较分析。
Sentiment Analysis is currently a vital area of research. With the advancement in the use of the internet, the creation of social media, websites, blogs, opinions, ratings, etc. has increased rapidly. People express their feedback and emotions on social media posts in the form of likes, dislikes, comments, etc. The rapid growth in the volume of viewer-generated or user-generated data or content on YouTube has led to an increase in YouTube sentiment analysis. Due to this, analyzing the public reactions has become an essential need for information extraction and data visualization in the technical domain. This research predicts YouTube Ad view sentiments using Deep Learning and Machine Learning algorithms like Linear Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). Finally, a comparative analysis is done based on experimental results acquired from different models.
