Media based sentiment indices as an alternative measure of consumer confidence

The world is currently generating data at an uprecedented rate. Embracing the data revolution, case studies on the construction of alternative consumer confidence indices using large text datasets have started to make its way into the academic literature. These 'sentiment indices' are constructed using text-based analysis. A subfield within computational linguistics. In this paper we consider the feasibility of constructing online sentiment indices using large amounts of media data as an alternative for the conventional survey method in South Africa. A clustering framework is adopted to provide an indication of feasible cadidate sentiment indices that best reflect the traditional survey based confidence consumer index conducted by the BER. The results indicate that the best candidate indices are linked to a single data source with a focus on using specialised financial dictionaries. Finally, composite indices for consumer confidence is constructed using Principle Component Analysis. The resulting indices' high correlation with the traditional consumer confidence index provide motivation for using media data sources to track consumer confidence within an emerging market such as South Africa using sentiment based techniques