Textual and contextual analysis of professionals’ discourses on XBRL data and information quality

Abstract

PurposeThe purpose of this study is to gain insight into what aspects of eXtensible Business Reporting Language (XBRL) data and information quality (DIQ) most interest professionals.Design/methodology/approachThe authors use text analytics to examine XBRL discourses from professionals working in the domain. They explore the discussion in the three largest LinkedIn XBRL groups. Data collection covered the period 2010-2016.FindingsVia the text analytics, the authors find the most appropriate XBRL DIQ dimensions. They propose an XBRL DIQ framework containing 18 relevant DIQ dimensions derived from both the accounting and IS fields. The findings of this study are expected to help direct future XBRL research into the DIQ dimensions most worthy of further empirical investigation.Originality/valueXBRL is the international standard for the digital reporting of financial, performance, risk and compliance information. Although the expectations of XBRL to produce improvements in DIQ via its applications (e.g. standard business reporting, digital data standard and interactive data visualization) are high, they remain unclear. This paper contributes to better understanding of the aspects of XBRL DIQ most relevant to professionals.