Designing Better Credibility Indicators: Understanding How Emerging Adults Assess Source Credibility of Misinformation Identification and Labeling

The proliferation of misinformation on social media platforms has impeded essential access to reliable information in the domains of health, elections, and politics. Recent advancements in generative AI and the propagation of AI-generated content (AIGC) have intensified the problem with the ease with which they can produce misinformation that is resilient to existing information assessment strategies. Content labels have become a preeminent means to indicate the credibility of social media posts. Emerging adults (ages 18-25) are ardent social media consumers, yet prior work has shown that credibility indicators are less impactful on this age group. My dissertation aims to better understand how emerging adults evaluate sources of misinformation identification and labels in order to offer insights into how to design better credibility assessment tools.