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The Use of Word Lists in Textual Analysis

Forthcoming in the Journal of Behavioral Finance

33 Pages Posted: 17 Jul 2014 Last revised: 2 Feb 2015

Tim Loughran

University of Notre Dame

Bill McDonald

University of Notre Dame - Mendoza College of Business - Department of Finance

Date Written: February 1, 2015

Abstract

A commonly-used platform to assess the tone of business documents in the extant accounting and finance literature is Diction. We argue that Diction is inappropriate for gauging the tone of financial disclosures. About 83% of the Diction optimistic words and 70% of the Diction pessimistic words appearing in a large 10-K sample are likely misclassified. Frequently occurring Diction optimistic words like respect, security, power, and authority will not be considered positive by readers of business documents. Similarly, over 45% of the Diction pessimistic 10-K word-counts are not and no. The Loughran-McDonald (2011) dictionary appears better at capturing tone in business text than Diction.

Keywords: Diction; word lists; sentiment analysis; Form 10-Ks; textual analysis

JEL Classification: C18, G14, M41

Suggested Citation

Loughran, Tim and McDonald, Bill, The Use of Word Lists in Textual Analysis (February 1, 2015). Forthcoming in the Journal of Behavioral Finance. Available at SSRN: https://ssrn.com/abstract=2467519 or http://dx.doi.org/10.2139/ssrn.2467519

Tim Loughran (Contact Author)

University of Notre Dame ( email )

Department of Finance
245 Mendoza College of Business
Notre Dame, IN 46556-5646
United States
574-631-8432 (Phone)
574-631-5255 (Fax)

Bill McDonald

University of Notre Dame - Mendoza College of Business - Department of Finance ( email )

P.O. Box 399
Notre Dame, IN 46556-0399
United States

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