Does mainstream news influence markets?
A semantic normalization based sentiment approach
COMP4560 PresentationSupervisor: Dr Timothy GrahamZhiheng Zhou
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Project Introduction • News may affect stock market price
• Apple, Google, Amazon, Microsoft
Project methodology
• Extract news data of above four companies. Combine, order them by date time
• Get score of each daily news by sentiment analyze approach
• Compare score plot to stock market price plot
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Sentiment analysis approach
• Original sentiment score function
• Using semantic normalization to improve sentiment score function
• Evaluation of the improvement
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Original Sentiment score function
• hu and liu [2] positive and negative dictionary
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• I love Apple.0 +1 0 total score: 1
Example
Using semantic normalization to improve sentiment score function
• Thesaurus (Synonyms dictionary) [3]• Hypernyms [4]• N-grams (multiple key words)• Grammatical modifier (not, very)
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Hypernyms and hyponyms example
• Kind of like the generic term and instance term
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N-grams example
• I look forward to getting the new iPhone.
• Look, forward, to : neutral
• Look forward to : positive
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Grammatical modifier
• I do not like Apple.
• Like : positive
• Not like : negative
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Evaluation --Granger causality test
• The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another.
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Project outcomes
Thanks for your watching.
Reference:[1] http://tozalezy.pl/index.php/the-news-impact-on-stock-prices/[2] Hu and Liu, KDD-2004[3] http://www.thesaurus.com[4] https://en.wikipedia.org/wiki/Hyponymy_and_hypernymy