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Twitter mood predicts the stock market

Johan Bollen, Huina Mao, Xiao-Jun Zeng

2010 · arXiv

PsychologyEconomicsStatistics & probability
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From the abstract

Behavioral economics tells us that emotions can profoundly affect individual behavior and decision-making. Does this also apply to societies at large, i.e., can societies experience mood states that affect their collective decision making? 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. negative mood and Google-Profile of Mood States (GPOMS) that measures mood in terms of 6 dimensions (Calm, Alert, Sure, Vital, Kind, and Happy). 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 2008. 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 87.6% in predicting the daily up and down changes in the closing values of the DJIA and a reduction of the Mean Average Percentage Error by more than 6%.

Metadata: arXiv. Abstracts retain their original authors’ rights.

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4 selected excerpts · 4 total mentions

izyda
Recommendation · rule
No, actually, I am referring to real time sentiment analysis of any kind - services such as http://www.dataminr.com/ or http://www.infotrie.com/ do this today mostly using online chatter, which you correctly point out probably would not be possible 5 years ago. However, real time news sentiment analysis would have been possible and relatively novel 5 years ago. For instance, Columbia's Paul Tetlock published a very interesting paper in the Journal of Finance in 2007 ago on the subject here: http://www0.gsb.columbia.edu/faculty/ptetlock/papers/Tetlock... (he used words from a Wall Street Journal column). If you read the paper, you'll find he used daily data over the 16…
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year period 1984-1999. While this is not of the same granularity you could get from services like InfoTrie or Dataminr, it certainly is of high enough granularity to trade on (and could have been done 10 years ago apparently!) and appears more useful than AAII or NAAIM. I am interested in your claim that the data has alpha and smart money is trading on it. I have been looking for any peer reviewed, academic articles actually documenting that alpha (ie. by anyone except the people trying to sell you the data). One such paper I found was Bollen et al's http://arxiv.org/abs/1010.3003. From my understanding, there are several problems with the methodology (I could find a rebuttal paper I read if you're interested) and the methodology was used in Derwent Capital - although the fund only traded it for 1 month: http://venturebeat.com/2012/05/28/twitter-fueled-hedge-fund-... Care to point me to anything else like that?
Original comment Can the Bloomberg Terminal be "Toppled"?
sogrady
Neutral mention · rule
where we agree then, i think, is the fact that Twitter's just another datapoint. and from a statistical perspective, it cannot be considered representative of the wider population for any number of reasons, not least the fact that it's observational rather than a random sample. that said, it's an interesting proxy for examining questions of sentiment, and its predictive ability has been examined several times academically within specific contexts (elections and markets - e.g. this one by Cornell http://arxiv.org/abs/1010.3003) and found to be relatively accurate. so agreed, it's not representative. but that doesn't mean it's not interesting and potentially useful.
Original comment MongoDB is the New MySQL
Caged
Neutral mention · rule
Here is the original paper - http://arxiv.org/pdf/1010.3003v1. The paper claims their code and data is open, but the link is broken and I was unable to find it by browsing their site...which seems to consist of mostly blank pages.
Original comment Twitter Mood Predicts The Stock Market

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