Journal of Business Accounting and Finance Perspectives

(ISSN: 2603-7475) Open Access Journal
JBAFP 2020, 2(2), 10; doi: 10.35995/jbafp2020010

Analyzing Microblogging Activity and Stock Market Behavior through Artificial Neural Networks

Received: 27 Aug 2019 / Revised: 23 Mar 2020 / Accepted: 2020-03-25 / Published: 2020-03-28
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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.
Keywords: microblog sentiment; S&P500; multi-layer perceptron neural network; Stanford CoreNLP Natural Language Processing; financial markets
OPEN ACCESS
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
CITE
Juan, P.-C.; Ángeles, L.-C.; Ada M, P.-P.; Marcos, V.-G. Analyzing Microblogging Activity and Stock Market Behavior through Artificial Neural Networks. JBAFP 2020, 2, 10.
Juan P-C, Ángeles L-C, Ada M P-P, Marcos V-G. Analyzing Microblogging Activity and Stock Market Behavior through Artificial Neural Networks. Journal of Business Accounting and Finance Perspectives. 2020; 2(2):10.
Juan, Piñeiro-Chousa; Ángeles, López-Cabarcos M; Ada M, Pérez-Pico; Marcos, Vizcaíno-González. 2020. "Analyzing Microblogging Activity and Stock Market Behavior through Artificial Neural Networks." JBAFP 2, no. 2: 10.
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