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Readability and Tone of UK Annual Report Data

dataset
posted on 30.11.2020, 10:54 by Ekaete EfretueiEkaete Efretuei
The dataset supports an existing published research. The data includes the textual analysis variables used. Details of the variables and data collection process is reported in the published article. Abstract below:

Abstract

In this study, I examine variations in the textual complexity of annual report narrative disclosures using the Fog Readability Index and Fin-Neg word list Tone Index given year and industry effects. I analyse accounting narrative Readability and Tone based on firm years, associations between the two narrative measures, and industry data. Tests of the relationship between Readability and Tone show that negative narratives have higher Readability scores, supporting the obfuscation hypothesis that bad news tends to be more difficult to read. A year analysis shows that the negative relationship between Readability and Tone increases in significance over time (2006–2011). An industry analysis shows that the observed obfuscation tends to persist in basic materials; consumer services; financial; technology; and utilities industries. This study shows that considering the effect of variations between industry and firm years can inform annual report textual complexity research and associated empirical analyses.

History

UoA

Business and Management