Cogent Social Sciences

Emerging Technologies for Transparency and Accountability in Multi-Source Entity Reporting

The rapid expansion of digital data has transformed how public, private and hybrid entities report, disclose, communicate and are evaluated. Governments, corporations, international organisations, civil society organisations, political actors and regulatory bodies now generate information across multiple channels, including official reports, sustainability disclosures, financial and non-financial statements, regulatory filings, media coverage, social media, open data portals, institutional websites and stakeholder-generated content. At the same time, emerging technologies such as artificial intelligence, machine learning, natural language processing, big data analytics, data mining, knowledge graphs, blockchain and visual analytics are reshaping how these diverse sources are collected, integrated and interpreted. This Article Collection focuses on the analysis of entity reporting through multiple sources and digital methods, with particular attention to how these technologies can support transparency, accountability, governance, risk assessment and evidence-based decision-making across social, political and organisational contexts.

This topic is important because reporting practices increasingly influence public trust, institutional legitimacy, regulatory oversight, political accountability and stakeholder decision-making. Yet entities often communicate through fragmented, inconsistent or strategically curated sources, making it difficult for researchers, regulators, citizens and decision-makers to assess the reliability, completeness and social meaning of reported information. Emerging technologies offer new opportunities to compare official disclosures with independent data sources, identify inconsistencies, detect risks, analyse large volumes of text and data, and reveal patterns that would be difficult to observe through traditional methods alone. However, these technologies also raise important ethical, political and methodological challenges, including algorithmic bias, data quality, privacy, misinformation, explainability, unequal access to digital capabilities and the risk of over reliance on automated analysis. Social science research is essential to understanding both the potential and the limitations of these tools.

This Collection welcomes interdisciplinary contributions examining how AI, big data and related technologies are used to analyse reporting by different types of entities across multiple sources. Relevant topics include AI-based analysis of institutional, political, corporate, regulatory and sustainability reporting; natural language processing of policy documents, annual reports, disclosures and public communications; multi-source data integration; open data and civic technologies; ESG and social responsibility reporting; detection of greenwashing, misinformation, symbolic compliance, corruption risks or reporting gaps; digital tools for public accountability and regulatory oversight; and responsible AI in reporting analysis. We particularly welcome original research articles, review articles, methodological papers, comparative studies, policy analyses and theoretically informed case studies. Contributions may come from politics and international relations, public administration, communication studies, sociology, accounting, management, law, information systems, data science and related social science fields.

When submitting to this Collection, please be sure to select both the name of the Collection, as well as the Media & Communication Studies section when prompted.

Professor Paula Gomes dos Santos’ research interests encompass reporting, accountability, and governance. Her work contributes to communication studies through its focus on disclosure practices, transparency, stakeholder communication, and the ways organisations construct, disseminate, and legitimise information across multiple channels.

Professor Fabio Albuquerque's work focuses on reporting, governance, accountability, and the role of information in institutional and organisational contexts. His research interests include transparency, entity reporting, digital transformation, and communication across multiple data sources, including official disclosures, media content, digital platforms, and stakeholder-generated information.

The Guest Advisors do not have conflicts of interest to disclose.

The Guest Advisors acknowledge that GPT-5.5 via IAedu/OpenAI API was used as a drafting and language support tool during the preparation of this Article Collection proposal. Its use was limited to idea development, text structuring and language refinement. The Guest Advisors supervised the process, reviewed and edited the proposal, verified its accuracy and relevance, and retained full responsibility for the final submitted version.

For more information about this Collection, please contact the Commissioning Editor, Dr. Molly Cole, at molly.cole@taylorandfrancis.com.