A Comparative Study on the Evaluation Functions of Chinese and Japanese Reported Speech Based on Big Data: Taking “Poverty Alleviation of China” as An Example

Abstract

Big data artificial intelligence technology has brought new ideas and perspectives to the study of journalism and communication and linguistics. Reported speech analysis is an important application in the intersection of linguistics and journalism and communication. This study selects the authoritative Chinese and Japanese media “People's Daily” and “Asahi Shimbun”, collects reports on “poverty alleviation of China” through big data technology, explores the similarities and differences of Chinese and Japanese reported speech by means of artificial intelligence deep learning text sentiment analysis. It is found that Chinese and Japanese news discourse have different preferences in sources, forms and settings, which are used to shape different images.