{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/b8d20c8211234da7841a777b525bd846\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/b8d20c8211234da7841a777b525bd846-f47cadc736d32fe3.gif","duration":278.641,"title":"Example User Journeys for Provenance and Fuzzy Provenance Solution","description":"In this video, I walk through four user journeys showcasing the importance of provenance and fuzzy provenance information in assessing text trustworthiness. I discuss scenarios involving AI-generated text, lack of origin information, and online matches to help users evaluate text credibility. No specific action is requested from viewers."}