Exploring inter-country connection in mass media: A case study of China

The development of theories and techniques for big data analytics offers tremendous possibility for investigating large-scale events and patterns that emerge over space and time. In this research, we utilize a unique open dataset “The Global Data on Events, Location and Tone” (GDELT) to model the image of China in mass media, specifically, how China has related to the rest of the world and how this connection has evolved upon time. The results of this research contribute to both the methodological and the empirical perspectives: We examined the effectiveness of the dynamic time warping (DTW) distances in measuring the differences between long-term mass media data. We identified four types of connection strength patterns between China and its top 15 related countries. With that, the distance decay effect in mass media is also examined and compared with social media and public transportation data. While using multiple datasets and focusing on mass media, this study generates valuable input regarding the interpretation of the diplomatic and regional correlation for the nation of China. It also provides methodological references for investigating international relations in other countries and regions in the big data era.