WEAK SIGNAL ANALYSIS: A REVIEW OF CURRENT APPROACHES

Abstract

The increase in the volume of data with which organizations work requires improving the processes of identifying future signals, such as events, trends and their relationships, through information analysis. The article considers the concept of weak signals as indicators of future changes that are difficult to detect at the initial stages, but over time they can become key trends that will influence the strategies of organizations. Methods for detecting weak signals are discussed, including Hiltunen's semiotic model, which considers signals in three dimensions: "problem", "signal" and "interpretation". The role of information technology in business analytics is noted as critical for forecasting future trends. Existing approaches to detecting weak signals using both qualitative and quantitative methods are analyzed, with an emphasis on modern techniques of text processing and keyword network analysis. It has been found that there is considerable potential to improve the methodologies and theoretical frameworks for detecting weak signals, which will enable us to more efficiently scan the environment and predict future changes