  Live video commenting is popular on video media platforms, as it can create a
chatting atmosphere and provide supplementary information for users while
watching videos. Automatically generating live video comments can improve user
experience and enable human-like generation for bot chatting. Existing works
mostly focus on short video datasets while ignoring other important video types
such as long videos like movies. In this work, we collect a new Movie Live
Comments (MovieLC) dataset to support research on live video comment generation
for long videos. We also propose a knowledge enhanced generation model inspired
by the divergent and informative nature of live video comments. Our model
adopts a pre-training encoder-decoder framework and incorporates external
knowledge. Extensive experiments show that both objective metrics and human
evaluation demonstrate the effectiveness of our proposed model. The MovieLC
dataset and our code will be released.
