Word Power: A New Approach for Content Analysis

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. Disciplines Finance | Finance and Financial ManagementThis journal article is available at ScholarlyCommons: https://repository.upenn.edu/fnce_papers/242Word Power: A New Approach for Content Analysis Narasimhan Jegadeesh Di Wu * July 2013ABSTRACT 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. * Narasimhan Jegadeesh is the Dean's Distinguished Professor at the Goizueta Business School, Emory University, and NBER, email: Jegadeesh@emory.edu This paper presents a new approach to determine the strength of various words in conveying negative or positive tone that is particularly suitable for finance and accounting applications. We objectively determine term weights based on market's reactions to 10-K filings. We apply our approach to determine the relative weights for the words in the lexicon to quantify the tone of 10-Ks.We find several new results with our approach. For much of our analysis, we compute term weights using the positive and negative word list compiled by Loughran and McDonald.Interestingly, the quantitative score that our approach assigns to various 10-Ks have very low correlation with the scores assigned by Loughran and McDonald using the same list of words.1 For example, the Harvard list classifies tax, cost, and liability as words with negative connotation but these words typically have a neutral connotation in finance and accounting.2 Available at http://www3.nd.edu/∼mcdonald/Word Lists.html 2 More importantly, our approach provides a more reliable measure of document tone than the earlier approaches. In particular, we find a significant relation between document tone and market reaction for the positive words, while none of the other papers in the literature have been successful in doing so. Additi...

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