Analyzing and Forecasting Emerging Technology Trends by Mining Web News

Abstract

Monitoring the development of existing technologies and discovering new and promising technologies help enterprises or firms obtain competitiveness in an environment of rapidly changing science. In other words, it is significant for a firm to promote a technology development strategy based on forecasting emerging technologies to gain competitive advantages while utilizing finite resources. In addition to the prospective changes, the speed and directions of technologies are considered to forecast future technology. Analyzing technically relevant historical information can be applied to identify how changes in technological developments are influenced by current and past changes in related technologies. An important aspect for identifying technological trends is the data. Among large amounts of data generated every day, Web news is an important data resource for studying social public awareness of emerging technologies. For this reason, this paper presents results of analyzing and forecasting emerging technology trends in Web news by utilizing burst detection algorithm, which is still impactful and significant in recent researches. After applying burst detection algorithm and clustering burst terms manually, we are able to detect and infer some main technological development trends for the near future, which are evaluated later by domain experts. That means the proposed method is effective and prospective for analyzing and forecasting technology trends.