Abstract-This paper covers design, implementation and evaluation of a system that may be used to predict future stock prices basing on analysis of data from social media services. The authors took advantage of large datasets available from Twitter micro blogging platform and widely available stock market records. Data was collected during three months and processed for further analysis. Machine learning was employed to conduct sentiment classification of data coming from social networks in order to estimate future stock prices. Calculations were performed in distributed environment according to Map Reduce programming model. Evaluation and discussion of results of predictions for different time intervals and input datasets proved efficiency of chosen approach is discussed here.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.