Exploring the spatial decay effect in mass media and location-based social media: A case study of China

Abstract

The rapid development of big data analytics provides tremendous possibilities to investigate large-scale patterns in both the spatial and temporal dimensions. In this research, we utilize a unique open dataset, the Global Database on Events, Location, and Tone (GDELT), and a geotagged social media dataset (Weibo) to analyze connections between Chinese provinces. Specifically, this study constructs a gravity model to compare the distance decay effect between the GDELT data (i.e., mass media data) and the Weibo data (i.e., location-based social media [LBSM] data). The results demonstrate that mass media data possess a weaker distance decay effect than LBSM data for Chinese provinces. This study generates valuable input to interpret regional relations in a fast-growing, developing country China. It also provides methodological references to explore urban relations in other countries and regions in the big data era.