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Exploring gender stereotypes in financial reporting: An aspect-level sentiment analysis using big data and deep

Fabiola Jeldes-Delgado1,2, Tiago Alves Ferreira3, David Diaz4

  • 1Escuela de Negocios Internacionales, Universidad de Valparaíso, Valparaíso, Chile.

Heliyon
|November 7, 2024
PubMed
Summary

Gender stereotypes significantly influence women's portrayal in financial reports, driven by economic conditions rather than corporate image management. Economic instability increases women's representation, while financial inclusion shows a positive correlation.

Keywords:
Aspect-level sentiment analysisBig dataDeep learningFinancial reportsFirm performanceGender inclusionGender stereotypesImpression managementSentiment analysis

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Area of Science:

  • Business and Finance
  • Computer Science
  • Sociology

Background:

  • Financial reports often contain qualitative information, or 'soft information,' that influences stakeholder perceptions.
  • The visual elements within financial reports, such as images, represent a significant component of this soft information.
  • Understanding the factors influencing image selection is crucial for interpreting the information conveyed in corporate disclosures.

Purpose of the Study:

  • To investigate the impact of gender stereotypes and economic factors on the representation of women in financial report imagery.
  • To analyze the relationship between corporate impression management strategies and the visual portrayal of women.
  • To assess the alignment of image selection practices with accounting neutrality principles.

Main Methods:

  • Aspect-level sentiment analysis applied to Big Data comprising 129,251 human face images from 2,085 financial reports in Chile.
  • Utilization of Deep Learning techniques for image analysis and feature extraction.
  • Correlation analysis between image representation, economic indicators, and financial inclusion metrics.

Main Results:

  • Gender stereotypes and external economic factors significantly shape the portrayal of women, overriding corporate impression management efforts.
  • Economic expansion correlates with decreased representation of women, while economic instability increases it.
  • Higher financial inclusion of women positively correlates with their presence in report images, indicating a bias in image selection.

Conclusions:

  • Image selection in financial reports is influenced by gender stereotypes and economic cycles, not solely by intentional corporate communication.
  • The findings suggest a deviation from the neutrality principles espoused by the International Accounting Standards Board (IASB).
  • This research offers novel insights into gender stereotypes, financial report soft information, and business impression management through a Big Data and Deep Learning lens.