Unemployment rate predictions are a key part of a government’s ability to make decisions and determine policies. That’s especially true in difficult economic times. Recently, a group of researchers from China proposed a method of forecasting unemployment rates using search engine query data.
In a paper titled “A Neural Network Based Forecasting Method For the Unemployment Rate Prediction Using the Search Engine Query Data”, presented at the 2011 IEEE International Conference in e-Business Engineering (ICEBE 2011), authors Wei Xu, Tingting Zheng, and Ziang Li describe a data mining-based framework using web search information to predict unemployment rates. Their tests show that a data mining method, such as neural networks, can be used together with web information as a tool for forecasting social/economic hotspots. Xu, Zheng, and Li demonstrate that the methodology can also be applied to other fields such as the real estate market, crude oil market, and foreign exchange market.
Papers from ICEBE 2011 are available to both IEEE Computer Society members and paid subscribers via the Computer Society Digital Library.