Forecasting economic indicators using a consumer sentiment index: Survey-based versus text-based data

Abstract

Given the confirmed effectiveness of the survey-based consumer sentiment index (CSI) as a leading indicator of real economic conditions, the CSI is actively used in making policy judgments and decisions in many countries. However, although the CSI offers qualitative information for presenting current conditions and predicting a household's future economic activity, the survey-based method has several limitations. In this context, we extracted sentiment information from online economic news articles and demonstrated that the Korean cases are a good illustration of applying a text mining technique when generating a CSI using sentiment analysis. By applying a simple sentiment analysis based on the lexicon approach, this paper confirmed that news articles can be an effective source for generating an economic indicator in Korea. Even though cross-national comparative research results are suited better than national-level data to generalize and verify the method used in this study, international comparisons are quite challenging to draw due to the necessary linguistic preprocessing. We hope to encourage further cross-national comparative research to apply the approach proposed in this study.