Title :
Sentiment analysis in financial markets A framework to utilize the human ability of word association for analyzing stock market news reports
Author :
Uhr, Patrick ; Zenkert, Johannes ; Fathi, Madjid
Author_Institution :
Inst. of Knowledge Based Syst., Univ. of Siegen, Siegen, Germany
Abstract :
As financial markets getting faster and more complex, it is difficult for market participants to manage the information overload. Sentiment analysis is a useful text mining method to process textual content and filter the results with analysis methods to relevant and meaningful information. The paper in hand introduces a new method for sentiment analysis in financial markets which combines word associations and lexical resources. Based on stock market news from January 2000 to February 2014 we analyzed documents on different levels. The results are presented and evaluated in this paper.
Keywords :
data mining; financial data processing; natural language processing; stock markets; text analysis; financial markets; human ability; information overload management; lexical resources; sentiment analysis; stock market news report analysis; text mining method; textual content processing; word association; Algorithm design and analysis; Companies; Databases; Portfolios; Sentiment analysis; Software; Text mining; Sentiment Analysis; Text Mining; Word Association;
Conference_Titel :
Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
Conference_Location :
San Diego, CA
DOI :
10.1109/SMC.2014.6974028
