Word power: A new approach for content analysis
We present a new approach for content analysis to quantify document tone. We find a significant relation between our measure of the tone of 10-Ks and market reaction for both negative and positive words. We also find that the appropriate choice of term weighting in content analysis is at least as im...
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Published in | Journal of financial economics Vol. 110; no. 3; pp. 712 - 729 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.12.2013
Elsevier Sequoia S.A |
Subjects | |
Online Access | Get full text |
ISSN | 0304-405X 1879-2774 |
DOI | 10.1016/j.jfineco.2013.08.018 |
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Abstract | We present a new approach for content analysis to quantify document tone. We find a significant relation between our measure of the tone of 10-Ks and market reaction for both negative and positive words. We also find that the appropriate choice of term weighting in content analysis is at least as important as, and perhaps more important than, a complete and accurate compilation of the word list. Furthermore, we show that our approach circumvents the need to subjectively partition words into positive and negative word lists. Our approach reliably quantifies the tone of IPO prospectuses as well, and we find that the document score is negatively related to IPO underpricing. |
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AbstractList | We present a new approach for content analysis to quantify document tone. We find a significant relation between our measure of the tone of 10-Ks and market reaction for both negative and positive words. We also find that the appropriate choice of term weighting in content analysis is at least as important as, and perhaps more important than, a complete and accurate compilation of the word list. Furthermore, we show that our approach circumvents the need to subjectively partition words into positive and negative word lists. Our approach reliably quantifies the tone of IPO prospectuses as well, and we find that the document score is negatively related to IPO underpricing. [PUBLICATION ABSTRACT] All rights reserved, Elsevier We present a new approach for content analysis to quantify document tone. We find a significant relation between our measure of the tone of 10-Ks and market reaction for both negative and positive words. We also find that the appropriate choice of term weighting in content analysis is at least as important as, and perhaps more important than, a complete and accurate compilation of the word list. Furthermore, we show that our approach circumvents the need to subjectively partition words into positive and negative word lists. Our approach reliably quantifies the tone of IPO prospectuses as well, and we find that the document score is negatively related to IPO underpricing. [PUBLICATION ABSTRACT] We present a new approach for content analysis to quantify document tone. We find a significant relation between our measure of the tone of 10-Ks and market reaction for both negative and positive words. We also find that the appropriate choice of term weighting in content analysis is at least as important as, and perhaps more important than, a complete and accurate compilation of the word list. Furthermore, we show that our approach circumvents the need to subjectively partition words into positive and negative word lists. Our approach reliably quantifies the tone of IPO prospectuses as well, and we find that the document score is negatively related to IPO underpricing. |
Author | Jegadeesh, Narasimhan Wu, Di |
Author_xml | – sequence: 1 givenname: Narasimhan surname: Jegadeesh fullname: Jegadeesh, Narasimhan email: Jegadeesh@emory.edu organization: Finance at the Goizueta Business School, Emory University and NBER, United States – sequence: 2 givenname: Di surname: Wu fullname: Wu, Di email: wudi1@wharton.upenn.edu organization: Finance at The Wharton School, University of Pennsylvania, United States |
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SubjectTerms | Content analysis Initial public offering Initial public offerings Language Lexicons Market analysis Market theory Pricing Studies Subjectivity Term weighting |
Title | Word power: A new approach for content analysis |
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