Difference between revisions of "Proposal yuzhou xin"
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[[User:Yxin|Yuzhou Xin]] | [[User:Yxin|Yuzhou Xin]] | ||
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== Introduction == | == Introduction == | ||
| − | Our emotions affect our actions. In this project, I would like to apply sentiment analysis techniques to study the general emotional state of LiveJournal,a virtual community, and use the result as a predictor for the financial market. Specifically, I would like to see if | + | Our emotions affect our actions. In this project, I would like to apply sentiment analysis techniques to study the general emotional state of LiveJournal,a virtual community, and use the result as a predictor for the financial market. Specifically, I would like to see if non-neutral emotional state of the community can be a good predictor for volatility in the US equity market. Also, can we extend the result to global markets. For example, can the anxiety in U.S. community affect markets in Europe or Asia. This will be an extension of the research done by Eric Gilbert and Karrie Karahalios. |
== Dataset == | == Dataset == | ||
In the beginning, I'll reuse the JiveJournal dataset gathered by Gilbert. | In the beginning, I'll reuse the JiveJournal dataset gathered by Gilbert. | ||
| − | [http://social.cs.uiuc.edu/people/gilbert/38] | + | Gilbert's data [http://social.cs.uiuc.edu/people/gilbert/38] |
| − | [http://www.livejournal.com/] | + | Livejournal's website [http://www.livejournal.com/] |
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== Proposed Work == | == Proposed Work == | ||
| − | We need to first build | + | We need to first build emotion indicators/index for the LiveJournal community using sentiment analysis techniques. We need to find ways to classify the community emotion as either neutral or non-neutral(happy/sad). Then we need to apply a learning algorithm to the indicators so that we can use them to predict market volatility. In the end, we want to check their predictive powers on US/Global market. If possible, we would like to use data from another community to see if it still supports our hypothesis. |
== Related Work == | == Related Work == | ||
| + | |||
| + | Similar work has done by Eric Gilbert and Karrie Karahalios in their paper Widespread Worry and the Stock Market. They combined a boost decision tree and a NB classifier to form a predictor for anxiety. Then they try to use it to predict stock market downward movement. | ||
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| + | == References == | ||
Widespread Worry and the Stock Market by Eric Gilbert and Karrie Karahalios[http://social.cs.uiuc.edu/people/gilbert/38] | Widespread Worry and the Stock Market by Eric Gilbert and Karrie Karahalios[http://social.cs.uiuc.edu/people/gilbert/38] | ||
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Latest revision as of 23:38, 1 February 2011
Sentiment in Blogging Community and Wall Street
Team Members
Introduction
Our emotions affect our actions. In this project, I would like to apply sentiment analysis techniques to study the general emotional state of LiveJournal,a virtual community, and use the result as a predictor for the financial market. Specifically, I would like to see if non-neutral emotional state of the community can be a good predictor for volatility in the US equity market. Also, can we extend the result to global markets. For example, can the anxiety in U.S. community affect markets in Europe or Asia. This will be an extension of the research done by Eric Gilbert and Karrie Karahalios.
Dataset
In the beginning, I'll reuse the JiveJournal dataset gathered by Gilbert. Gilbert's data [1] Livejournal's website [2]
Proposed Work
We need to first build emotion indicators/index for the LiveJournal community using sentiment analysis techniques. We need to find ways to classify the community emotion as either neutral or non-neutral(happy/sad). Then we need to apply a learning algorithm to the indicators so that we can use them to predict market volatility. In the end, we want to check their predictive powers on US/Global market. If possible, we would like to use data from another community to see if it still supports our hypothesis.
Related Work
Similar work has done by Eric Gilbert and Karrie Karahalios in their paper Widespread Worry and the Stock Market. They combined a boost decision tree and a NB classifier to form a predictor for anxiety. Then they try to use it to predict stock market downward movement.
References
Widespread Worry and the Stock Market by Eric Gilbert and Karrie Karahalios[3]
