Journal of Accounting, Finance & Management Strategy





Volume 10, Number 2, December 2015

eWOM for Stock Market by Big Data Methods


This study utilized Internet big data to investigate the effects of positive and negative emotions in electronic word-of-mouth (eWOM) on the stock price and trading volume of listed companies, from a behavioral finance perspective. The study was conducted for three months from June 1, 2014 to August 31, 2014. The ten most representative stocks in Taiwan's electronics industry were selected, with 182,769 values of data obtained from Internet big data. The results revealed that total eWOM had a significant correlation with, and impact on, stock trading volume. Both the net and net negative eWOM had correlation with, and impact on, stock price, and both exhibited predictive effects, which could be used as a reference to assist investors and securities firms in their prediction of stock price and trading volume.

Keywords: Big Data, Behavioral Finance, Electronic Word of Mouth, eWOM, Forecast

JEL Classification: E27, E37, G02