@Article{
AUTHOR = {Juan, Piñeiro-Chousa Juan and Ángeles, López-Cabarcos M Ángeles and Ada M, Pérez-Pico Ada M and Marcos, Vizcaíno-González Marcos},
TITLE = {Analyzing Microblogging Activity and Stock Market Behavior through Artificial Neural Networks},
JOURNAL = {Journal of Business Accounting and Finance Perspectives},
VOLUME = {2},
YEAR = {2020},
NUMBER = {2},
PAGES = {0--0},
URL = {https://jbafp.archive.jams.pub/article/2/2/53},
ISSN = {2603-7475},
ABSTRACT = {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.},
DOI = {10.35995/jbafp2020010}
}