Traditional or social media: which capture employment better?

Abstract

Political discourse has the ability to spread either uncertainty or calm among the population. Economic upheavals of considerable magnitude can also spread ambiguity. Both newspaper articles and Twitter posts reflect important events that have the potential to increase or decrease uncertainty from a citizen’s perspective. We employ two measures of media uncertainty, one reflecting the uncertainty perceived by journalists and the other characterizing the uncertainty associated with Twitter users. More specifically, we use the Twitter Economic Uncertainty and the Economic Policy Uncertainty Index. To investigate which uncertainty source better captures employment variations, we apply a regression decision tree and linear regression. Our results speak in favour of the more traditional media uncertainty source. Linear regression outperforms the decision tree in both models. Namely, we find a statistically significant negative relationship between both uncertainty measures and employment, while controlling for other macroeconomic aspects.

Keywords

• economic policy uncertainty
• employment
• ,machine learning
• decision tree
• twitter economic uncertainty