A method for aggregating the features of bullet screen

Abstract

Bullet screen is a new type of comment appearing on video websites. When the video is played, it will be displayed in real time. Through sentimental analysis of the screen, we can quickly understand the sentimental types of the current video. However, it is unrealistic to deal with all the bullet screens of the whole video at one time with traditional methods. This paper proposes a method of aggregating all text content in video to represent very long video content to achieve video feature extraction. The method proposed in this paper is more effective than PCA and scalable methods in reducing dimension and achieving aggregation.