Critical Insights Into the Design of Big Data Analytics Research: How Twitter “Moods” Predict Stock Exchange Index Movement

A PROOF OF PRINCIPLE STUDY Predicting stock market movements has motivated researchers and practitioners to formulate new models and methodologies (Atsalakis, Dimitrakakis, & Zopounidis, 2011). The daily fluctuations of the Dow Jones Industrial Average (DJIA) was predicted with an 86,7% accuracy using Twitter public moods by Bollen, Mao and Zeng (2011). Research into public moods has been of interest to academics from several disciplines, such as psychology (Stolarski, Matthews, Postek, Zimbardo, & Bitner, 2014), social science (Johnston & Newman, 2014), politics (Ellis & Faricy, 2011), and information sciences (Li, Wang, Li, Liu, Gong, & Chen, 2014). Practitioners from government (Hakhverdian, 2012) and industry (Bollen, Mao, & Zeng, 2011) appear to be interested in public moods, and their effects.