Social Media Semantics: Enhancing Manipulated Media Detection Through An Artificial Intelligence Weakness
Year: 2025
Type: article
Abstract: As fake news and disinformation continue to proliferate in digital journalism, the development of artificial intelligence (AI) analytics to identify synthetic content inconsistencies is increasingly important. This study explores trained AI analytics’ struggle to detect semantic gaps within AI-generated media. Findings reinforce human semantic capabilities and a direction for detection tools. AI analytics designed for semantic detection-related tasks are evaluated through the application of the Theory of Content Consistency, with insights for combatting social media news truth erosion.
Source: Electronic News
Authors: Regina Luttrell, Jason Davis, Carrie Welch
Institution: Syracuse University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4412470003