Difference between revisions of "Gilbert et al., ICWSM 2010"
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[http://social.cs.uiuc.edu/people/gilbert/pub/icwsm10.worry.gilbert.pdf Widespread Worry and the Stock Market] <br> | [http://social.cs.uiuc.edu/people/gilbert/pub/icwsm10.worry.gilbert.pdf Widespread Worry and the Stock Market] <br> | ||
[http://social.cs.uiuc.edu/people/gilbert/38 Website for the paper] | [http://social.cs.uiuc.edu/people/gilbert/38 Website for the paper] | ||
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== Summary == | == Summary == | ||
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The stock market usually reflects business fundamentals, such as corporate earnings. However, we also see many events that seem rooted in human emotion more than anything else, from “irrational exuberance” during booms to panicked sell-offs during busts. In this paper, Gilbert et al attempt to [[AddressesProblem:: explain the downward movement of stock prices using sentiment analysis methods]]. He [[UsesMethod::build an anxiety index for LiveJournal, an active blogging community]]. Then, they correlated their anxiety index to the S&P 500. | The stock market usually reflects business fundamentals, such as corporate earnings. However, we also see many events that seem rooted in human emotion more than anything else, from “irrational exuberance” during booms to panicked sell-offs during busts. In this paper, Gilbert et al attempt to [[AddressesProblem:: explain the downward movement of stock prices using sentiment analysis methods]]. He [[UsesMethod::build an anxiety index for LiveJournal, an active blogging community]]. Then, they correlated their anxiety index to the S&P 500. | ||
== Brief description of the method == | == Brief description of the method == | ||
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There are two main parts involved in predicting stock market movement base on anxiety | There are two main parts involved in predicting stock market movement base on anxiety | ||
* Boost Decision Tree | * Boost Decision Tree | ||
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== Experimental result == | == Experimental result == | ||
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The resulted predictions are tested using Granger-causal analysis, which use econometric techniques to tell whether the Anxiety Index provides useful information for projecting future stock market prices not already contained in the market itself. Statistically, this paper showed that in general moods from an online community has novel predictive information about the stock market. | The resulted predictions are tested using Granger-causal analysis, which use econometric techniques to tell whether the Anxiety Index provides useful information for projecting future stock market prices not already contained in the market itself. Statistically, this paper showed that in general moods from an online community has novel predictive information about the stock market. | ||
== Dataset == | == Dataset == | ||
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LiveJournal post stream gathered using atom listener on: [http://atom.services.livejournal.com/atom-stream.xml LiveJournal atom stream] | LiveJournal post stream gathered using atom listener on: [http://atom.services.livejournal.com/atom-stream.xml LiveJournal atom stream] | ||
[[UsesDataset:: LiveJournal post stream gathered using atom listener]] | [[UsesDataset:: LiveJournal post stream gathered using atom listener]] | ||
Revision as of 17:38, 11 February 2011
This a Paper discussed in Social Media Analysis 10-802 in Spring 2011.
Contents
Citation
Title : Widespread Worry and the Stock Market Authors : Eric Gilbert, Karrie Karahalios Conference : ICWSM 2010
Online version
Widespread Worry and the Stock Market
Website for the paper
Summary
The stock market usually reflects business fundamentals, such as corporate earnings. However, we also see many events that seem rooted in human emotion more than anything else, from “irrational exuberance” during booms to panicked sell-offs during busts. In this paper, Gilbert et al attempt to explain the downward movement of stock prices using sentiment analysis methods. He build an anxiety index for LiveJournal, an active blogging community. Then, they correlated their anxiety index to the S&P 500.
Brief description of the method
There are two main parts involved in predicting stock market movement base on anxiety
- Boost Decision Tree
- bagged complement Naive Bayes algorithm
After training on the data set, the author used a combination of these 2 classifiers to assess the anxiety level of the blogging community.
To check accuracy, the author used Granger-causal Analysis to test whether anxiety level gave good information to movements on stock market.
Experimental result
The resulted predictions are tested using Granger-causal analysis, which use econometric techniques to tell whether the Anxiety Index provides useful information for projecting future stock market prices not already contained in the market itself. Statistically, this paper showed that in general moods from an online community has novel predictive information about the stock market.
Dataset
LiveJournal post stream gathered using atom listener on: LiveJournal atom stream LiveJournal post stream gathered using atom listener
Related Papers
There has been a lot of work on using sentiment analysis to predict the stock market.
- The paper by Chua, Milosavljevic and Curran Uses bayes classifiers to classify the sentiment of a internet stock message board.
