Media Framing and Digital Astroturf: Developing Diagnostic Constructs for Measuring Corporate Environmental Misrepresentation across Social Media and Digital Campaigns

• Adaan Ahsun

  Covenant University

  Author

The proliferation of corporate environmental claims on social media platforms has created an unprecedented information environment where authentic sustainability commitments coexist with sophisticated misrepresentation strategies. This study addresses the critical gap in existing measurement frameworks by developing and validating diagnostic constructs for detecting corporate environmental misrepresentation across digital media ecosystems. Grounded in framing theory and legitimacy theory, the research employs a mixed-methods design combining content analysis of 1,247 social media posts from 47 multinational corporations with computational linguistic analysis of framing patterns. The proposed diagnostic framework achieves 89.4% accuracy in identifying coordinated astroturfing campaigns through the integration of linguistic, network, and temporal indicators. Key findings reveal that digital astroturfing operations exhibit distinct framing signatures—including manufactured grassroots sentiment, selective disclosure patterns, and coordinated amplification networks—that can be systematically measured and distinguished from authentic stakeholder engagement. The validated constructs provide practitioners, regulators, and researchers with actionable tools for enhancing transparency in corporate environmental communication. This research contributes to the growing body of literature on greenwashing detection while offering practical mechanisms for enforcing environmental integrity in digital spaces.

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Copyright (c) 2026 Adaan Ahsun (Author)

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