Using Stata and WordStat to analyze Twitter data to assess economic sentiment

By Lydia Pik Yi Cheung & David White

In this session David White and his co-author, Lydia Pik Yi Cheung present their methodology and techniques used to create a conceptual approach to assess macro-economic sentiment using Twitter data.
David and Lydia show how to use Stata’s Python integration to extract historical data from Twitter, clean the data in readiness for analysis in WordStat. The WordStat sentiment dictionary was then used to assess economic sentiment and create results that allowed comparison to existing economic indicators.

Dr. Lydia Pik Yi Cheung is a senior lecturer and academic researcher in the School of Economics at the Auckland University of Technology, with a focus in Industrial Organization, Competition Economics, and Applied Microeconomics. She graduated summa cum laude from Boston University and obtained her Ph.D. in Economics from the University of Minnesota.

David White is a Director of Survey Design and Analysis Services (SDAS), the distributor of WordStat, QDA Miner, Stata in Australia, Indonesia and New Zealand. David is an independent consultant providing training and advisory services in data analytics, IT risk management, IT assurance.