Work

Computer-based analysis of the strategic content of UK annual report narratives

Year: 2014

Type: conference-paper

Abstract: This project uses computer-based natural language processing (NLP) methods to analyse the content of annual report narrative disclosures by UK firms listed on the London Stock Exchange. Company law requires UK firms publish an annual report containing audited financial statements together with substantial narrative disclosures on a range of business and governance related topics. Published annual reports represent the most comprehensive systematic disclosure made by UK firms to shareholders and as such attract considerable attention from academic researchers, regulators, and the financial media. Other stakeholder groups including employees, creditors, customers, suppliers, etc. also rely in various degrees on these disclosures.

Source: Lancaster EPrints (Lancaster University)

Authors: Mahmoud El‐Haj, Vasiliki E. Athanasakou, Paul Rayson, Steve Young, Martin Walker

Institution: University of Manchester

Language: English

Topic: Computational and Text Analysis Methods

Subfield: General Social Sciences

Field: Social Sciences

Domain: Social Sciences

Open Access status: green

Funder: Economic and Social Research Council

Award: Understanding the Influences of Financial Reporting, Corporate Disclosures and Financial Media on the Corporate Financial Information Environment

OpenAlex ID: W133240409