  To characterize economic development and diagnose the economic health
condition, several popular indices such as gross domestic product (GDP),
industrial structure and income growth are widely applied. However, computing
these indices based on traditional economic census is usually costly and
resources consuming, and more importantly, following a long time delay. In this
paper, we analyzed nearly 200 million users' activities for four consecutive
years in the largest social network (Sina Microblog) in China, aiming at
exploring latent relationships between the online social activities and local
economic status. Results indicate that online social activity has a strong
correlation with local economic development and industrial structure, and more
interestingly, allows revealing the macro-economic structure instantaneously
with nearly no cost. Beyond, this work also provides a new venue to identify
risky signal in local economic structure.
