Twitter mood predicts the stock market johan bollen
Volume 2, Issue 1MarchPages 1—8. Behavioral economics tells us that emotions can profoundly affect individual behavior and decision-making.
Does this also apply to societies at large, i. By extension is the public mood correlated or even predictive of economic indicators? Here we investigate whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average DJIA over time.
We analyze the text content of daily Twitter feeds by two mood tracking tools, namely OpinionFinder that measures positive vs. We cross-validate the resulting mood time series by comparing their ability to detect the public's response to the presidential election and Thanksgiving day in A Granger causality analysis and a Self-Organizing Fuzzy Neural Network are then used to investigate the hypothesis that public mood states, as measured by the OpinionFinder and GPOMS mood time series, are predictive of changes in DJIA closing values.
Our results indicate that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions but not others. We find an accuracy of Johan Bollen is associate professor at the Indiana University School of Informatics and Computing.
He was formerly a staff scientist at the Los Alamos National Laboratory fromand an Assistant Professor at the Department of Computer Twitter mood predicts the stock market johan bollen of Old Dominion University from to He obtained his PhD in Experimental Psychology from the University of Brussels in on the subject of cognitive models of human hypertext navigation.
He has taught courses on Data Mining, Information Retrieval and Digital Calculating call option premium. His research has been funded by the Andrew W.
Mellon Foundation, National Science Foundation, Library of Congress, National Aeronautics and Space Administration and the Los Alamos National Laboratory.
Twitter mood predicts the stock market with % accuracy - Buzztalk
His present research interests are sentiment tracking, hmrc exchange rates march 2016 social science, usage data mining, informetrics, and digital libraries.
He has australian meat and livestock trading published on these subjects as well as matters relating to adaptive information systems architecture. He is presently the Principal Investigator of the Andrew W. Mellon Foundation and NSF funded MESUR project which aims to expand the quantitative tools available for the assessment of scholarly impact.
Twitter Mood as a Stock Market Predictor
Huina Mao is a Ph. Her research twitter mood predicts the stock market johan bollen is on electrical load forecasting and web mining. She has published on topics in fuzzy logic, expert systems, and utility load-forecasting.
She is presently working on public sentiment tracking from large-scale online, social networking environments stock trade wizard rapidshare the objective of modeling and predicting socio-economic indicators. Xiao-Jun Zeng received the B.
He has been with the University of Manchester since and is currently a Senior Lecturer in the School of Computer Science and the School of Informatics. From tohe was with Knowledge Support Systems KSS Ltd. He has published more than 60 journal and conference papers including 12 IEEE Transaction papers.
Zeng is an Associate Editor of the IEEE Trans. Screen reader users, click here to load entire article This page uses JavaScript to progressively load the article content as a user scrolls. Screen reader users, click the load entire article button to bypass dynamically loaded article content. Please note that Internet Explorer version 8. Please refer to this blog post for more information.
Twitter mood predicts the stock market. | BibSonomy
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