Cheng-jun Wang and Lingfei Wu
The increasing power of search engines has made advertisement more and more precise - computational advertising systems like Google AdSense collect and filter the attention of the most relevant users and sale it to companies. However, how to reach target customers in the physical world precisely is still a question remained unsolved in the advertising industry. In the current study we analyze the anonymized smartphone data of 10^5 Beijing residents in 30 days and correlate their physical movement with flow of attention in cyberspace. In particular, we use network renormalization technique to divide the city into local areas and use information entropy based measurements to identify the most relevant website visited in these local areas. To demonstrate the applied value of our research we create an interactive map that takes the queries of website names as input and lights up the most relevant areas as output. This tool is particularly useful for dot-com companies who are interested in buying outdoor advertising space.