%0 Journal Article
%A Juan, Piñeiro-Chousa Juan
%A Ángeles, López-Cabarcos M Ángeles
%A Ada M, Pérez-Pico Ada M
%A Marcos, Vizcaíno-González Marcos
%D 2020
%J Journal of Business Accounting and Finance Perspectives

%@ 2603-7475

%V 2
%N 2
%P 10

%T Analyzing Microblogging Activity and Stock Market Behavior through Artificial Neural Networks
%M doi:10.35995/jbafp2020010
%U https://jbafp.archive.jams.pub/article/2/2/53
%X This paper attempts to analyze the relationship between social network activity (message sentiment) and stock market (trading volume and risk premium). We used Artificial Neural Networks to analyze 87,511 stock-related microblogging messages related to S&P500 Index posted between October 2009 and October 2014. The results obtained suggest that there is a direct relationship between trading volume and negative sentiment, and between risk premium and negative sentiment. The paper concludes with several directions for future research.