Abstract
News stories about publicly traded companies are labeled positive or negative according to price changes of the company stock. It is shown that models based on lexical features can distinguish good news from bad news with accuracy of about 70%. Unfortunately, this works only when stories are labeled according to cotemporaneous price changes but does not work when they are labeled according to subsequent price changes.
Original language | English |
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Pages | 86-88 |
Number of pages | 3 |
State | Published - 2005 |
Event | 2004 AAAI Spring Symposium - Stanford, CA, United States Duration: 22 Mar 2004 → 24 Mar 2004 |
Conference
Conference | 2004 AAAI Spring Symposium |
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Country/Territory | United States |
City | Stanford, CA |
Period | 22/03/04 → 24/03/04 |