A data-driven short video international communication model based on indicator system communication network and attention BiLSTM neural network

As one of the most popular ways to disseminate Internet content in the current era of media convergence, short videos have increasingly become part of people’s daily lives. This paper takes TikTok as the research object, focusing on the study of short video communication process. The research objective of this paper is to improve the international communication effect of short videos through data-driven analysis and strategy research on the law of international communication of short videos. Firstly, the key objective indicator system about international communication of short videos is constructed, the definition, selection and design logic of key objective indicators are introduced, the construction idea of the corresponding indicator system is proposed, and then the key objective indicator system about international communication of short videos and related data set are constructed. Secondly, an international communication network model for short videos is built. The construction of this network model is divided into three steps, the construction of the short video communication network KOIS-PN based on the key objective indicators system, the construction of AT-BILSTM neural network model to adapt to the research scenario of short video international communication, the construction of an international communication network model of short videos combining KOIS-PN and AT-BILSTM. The international short video communication network is constructed according to the key objective index system of international short video, and the key objective index system is used as nodes in the communication network, and the short video communication network is constructed by hierarchical relationship. Thirdly, the performance of the core theoretical model proposed in this paper is verified. The experimental results show that, the KOISPN-ATBILSTM international communication network model of short videos has certain validity and advancement.

Jinbao Song, Jing Liu