A Study on Transnational Media Coverage of Sino-US Trade through Semantic Network Analysis

This study was conducted to analyze the perspectives of transnational media reporting on Sino-US trade. News reports from Associated Press and Xinhua Agency were collected March 20, 2018, October 31, 2018. Text mining frequency analysis performed by Python examine significant keywords news reports. Eigenvector centralities Modularity Gephi. QAP correlation analyses Ucinet. As a result, had different clusters. There between Semantic Network Network. supports two aspects. involved four sub-topics when trade frictions, namely China-related clusters, US-related trade-related tariff-related The three sub-topics, China-US Trade-related global economy-related focused while network structure AP shows positive correlation, which some extent indicates Chinese American reporting. division clusters difference in choice prominence words that are still affected political stance culture constructing framework strategy. Based these results, valuable implications provided for across countries.