Exploring Sentiment on Financial Market Through Social Media Stream Analysis

The aim of this chapter is to present the prototype developed in the TrendMiner project in the financial domain. TrendMiner is a Research & Development project co-funded by the European Commission under the 7th Framework Programme contract nr. FP7-ICT-287863. We developed a web-based prototype summarising the media stream in terms of its likely impact on a selected financial asset from economic and political-economic perspectives. The platform is able to gather the events occurring along the social media timeline and to build a tailored visualisation/summarisation of these data with price movements of a given stock or index. The results of the prototype have been evaluated and summarised in this chapter, and three examples are used as proof of concepts for validating the prototype outcomes against the known market behaviours and the existing literature. The TrendMiner financial use case prototype shows its ability to play as another decision support tool besides the consolidated market forecast techniques such as technical and fundamental analysis.

[1]  E. Fama EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[2]  Sofus A. Macskassy,et al.  More than Words: Quantifying Language to Measure Firms' Fundamentals the Authors Are Grateful for Assiduous Research Assistance from Jie Cao and Shuming Liu. We Appreciate Helpful Comments From , 2007 .

[3]  Susan G. Watts,et al.  Whisper Forecasts of Quarterly Earnings Per Share , 1999 .

[4]  H. Stanley,et al.  Quantifying Trading Behavior in Financial Markets Using Google Trends , 2013, Scientific Reports.

[5]  K. Vohs,et al.  Case Western Reserve University , 1990 .

[6]  Paul C. Tetlock Giving Content to Investor Sentiment: The Role of Media in the Stock Market , 2005, The Journal of Finance.

[7]  ChenHsinchun,et al.  Textual analysis of stock market prediction using breaking financial news , 2009 .

[8]  H. Simon,et al.  A Behavioral Model of Rational Choice , 1955 .

[9]  Tim Loughran,et al.  When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks , 2010 .

[10]  Hsinchun Chen,et al.  Textual analysis of stock market prediction using breaking financial news: The AZFin text system , 2009, TOIS.

[11]  Zhi Da,et al.  In Search of Attention , 2009 .

[12]  S. J. Motowidlo,et al.  Prosocial Organizational Behaviors , 1986 .

[13]  Steven Skiena,et al.  Large-Scale Sentiment Analysis for News and Blogs (system demonstration) , 2007, ICWSM.

[14]  Johan Bollen,et al.  Twitter mood predicts the stock market , 2010, J. Comput. Sci..

[15]  Eric Gilbert,et al.  Widespread Worry and the Stock Market , 2010, ICWSM.

[16]  Yigitcan Karabulut Can Facebook Predict Stock Market Activity? , 2013 .

[17]  Steven Skiena,et al.  Trading Strategies to Exploit Blog and News Sentiment , 2010, ICWSM.