An Empirical Study of Automatic Social Media Content Labeling and Classification based on BERT Neural Network

Web flow now is a very important success factor for social media marketing and thus more and more approaches for creating high web flow have been proposed in recent years. Automatic content generation (ACG) website is one of the possible approaches which can help to create web flow. In order to achieve the idea of automatic content generation website, web article classification has been considered the most important task. Therefore, we have development an empirical study to test the content labeling and article classification performance, which is based on the technique of BERT neural network. The performance evaluation including accuracy performance and time performance that are important for us to understand the possibility for implementing the ACG website in real environment, especially the possibility when dealing with large amount of data.