Text Data Sources in Archival Accounting Research: Insights and Strategies for Accounting Systems' Scholars

Abstract

ABSTRACT This paper reviews the emerging computer-aided text analysis (CATA) accounting literature through proposing a model of the corpus linguistic research production process, followed by analysis of the main text archival data sources in published papers in the Top Six accounting journals from 2010 to 2016. Reviewed papers appear in a 5 × 5 matrix that includes five categories of text data (i.e., SEC filings, conference call transcripts, earnings press releases, financial analyst reports, and other sources) and five categories of text measures (i.e., tone, readability, similarity, firm characteristics and environment, and other measures). A brief review of the CATA literature published in two AIS journals is followed by a summary of the tools and KS (knowledge and skills) observed in the reviewed research. Finally, we offer implications by discussing four issues related to CATA accounting research. We conclude that the emerging CATA accounting research offers unique opportunities for knowledgeable AIS scholars.