Detecting weak signals for long-term business opportunities using text mining of Web news

In an uncertain business environment, competitive intelligence requires peripheral vision to scan and identify weak signals that can affect the future business environment. Weak signals are defined as imprecise and early indicators of impending important events or trends, which are considered key to formulating new potential business items. However, existing methods for discovering weak signals rely on the knowledge and expertise of experts, whose services are not widely available and tend to be costly. They may even provide different analysis results. Therefore, this paper presents a quantitative method that identifies weak signal topics by exploiting keyword-based text mining. The proposed method is illustrated using Web news articles related to solar cells. As a supportive tool for the expert-based approach, this method can be incorporated into long-term business planning processes to assist experts in identifying potential business items.

► This paper proposes a method for weak signal detection using text mining. ► The method can be used for identifying the long-term business items. ► The method generates two types of keyword portfolio maps for weak signal detection. ► The method quantifies the procedure for identifying weak signals from Web news.