Impact of Social Media on the Stock Market: Evidence from Tweets

  • Vojtěch Fiala Department of Finance, Faculty of Business and Economics, Mendel university in Brno, Zemědělská 1, 613 00 Brno, Czech Republic, e-mail:
  • Svatopluk Kapounek Department of Finance, Faculty of Business and Economics, Mendel university in Brno, Zemědělská 1, 613 00 Brno
  • Ondřej Veselý Faculty of Business and Economics, Mendel university in Brno, Zemědělská 1, 613 00 Brno
Keywords: stock returns, Granger causality, text mining, sentiment analysis, CAPM


The paper deals with the impact of the economic agent sentiment on the return for Apple and Microsoft stocks. We employed text mining procedures to analyze Twitter messages with either negative or positive sentiment towards the chosen stock titles. Those sentiments were identified by developed algorithms which are capable of identifying sentiment towards companies and also counting the numbers of tweets in the same group. This resulted in counts of tweets with positive and negative sentiment. Then we ran analysis in order to find causality between sentiment levels and the stock price of companies. To identify causal effects we applied Granger causality tests. We found bilateral causality between the risk premium and the amount of news distributed by Twitter messages.


Aitchison, J. and Silvey, S. D. 1958. Maximum Likelihood Estimation of Parameters Subject to Restraints. Annals of Mathematical Statistics, 29, 813–828.

Antweiler, W. and Frank, M. Z. 2004. Is all that talk just noise? The information content of Internet stock message boards. Journal of Finance, 59, 1259–1294.

Arias, M., Arratia, A. and Xuriguera, R. 2013. Forecasting with Twitter Data. ACM Transactions on Intelligent Systems and Technology, 5 (1).

Berndt, E. R., Savin, N. E. 1977. Conflict Among Criteria for Testing Hypotheses in the Multivariate Linear Regression Model. Econometrica, 45 (5), 1263–1278.

Bollen, J., Mao, H. and Zeng, X. J. 2011. Twitter mood predicts the stock market. Journal of Computational Science, 1–8.

Chung, S. and Liu, S. 2011. Predicting Stock Market Fluctuations from Twitter: An analysis of the predictive powers of real-time social media. [online]. Available at: aldous/157/Old_Projects/Sang_Chung_Sandy_Liu.pdf. [Accessed 2015, February 16].

Dolan, R. J. 2002. Emotion, cognition, and behavior. Science, 298, 1191–1194.

Friedman, M. 1953. The case for flexible exchange rates. Essays in Positive Economics. University of Chicago Press, Chicago.

Fama, E. F. 1965. The Behavior of Stock-Market Prices. The Journal of Business, 38 (1), 34–105.

Fama, E. F. 1970. Efficient capital markets: a review of theory and empirical work. Journal of Finance, 25 (2), 383–417.

Fama, E. F. 1991. Efficient capital markets II. Journal of Finance, 46 (5), 1575–1617.

Gilbert, E. and Karahalios, K. 2010. Widespread Worry and the Stock Market. In Proceedings of the international conference on weblogs and social media (ICWSM 10).

Granger, C. W. J. 1969. Investigating causal relations by econometric models and cross-spectral models. Econometrica, 37, 424–438.

Kim, S. H. and Kim, D. K. 2014. Investor sentiment from internet message postings and the predictability of stock returns. Journal of Economic Behavior & Organization, 107, 708–729.

Kuleshov, V. 2011. Can Twitter predict the stock market? [online]. Available at: [Accessed 2015, February 16].

LeRoy, S. and Porter, R. 1981. The present-value relation: tests based on implied variance bounds. Econometrica, 49, 97−113.

Ross, S. A., 1976. The Arbitrage Theory of Capital Asset Pricing. Journal of Economic Theory, 13, 341–360.

Shiller, J. R. 1981. Do stock prices move too much to be justified by subsequent changes in dividends? American Economic Review, 71, 421−436.

Shiller, J. R. 2003. From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17 (1), 83–104.

Silvey, S. D. 1959. The Lagrange Multiplier Test. Annals of Mathematical Statistics, 30, 389–407.

Sims, C. 1972. Money, income, and causality. American Economic Review, 62, 540–552.

Wald, A. 1943. Tests of Hypotheses Concerning Several Parameters When the Number of Observations is Large. Transactions of the American Mathematical Society, 54, 426–482.

Zhang, X., Fuehres, H. and Gloor, P. 2011. Predicting Stock Market Indicators Through Twitter: “I hope it is not as bad as I fear”. Procedia – Social and Behavioral Sciences, 26, 55–62.