This thesis explores the perception and trustworthiness of the users towards artificial intelligence (AI) -generated content on social media platforms. The study employs the Technology Acceptance Model (TAM) and Framing Theory as theoretical frameworks to understand the factors influencing user attitudes and behaviours towards AI-generated content. The research explores three main areas: user trust in AI-generated content, the ability to differentiate between AI-generated and human-generated content and the ethical implications of AI-generated content use.

The research employed an online survey with 100 participants to collect quantitative data on their experiences and perceptions of AI-generated content. The findings indicate a range of trust levels in AI-generated content, with a general trend towards cautious acceptance. The results also reveal a gap between the participants' perceived and actual abilities to distinguish between AI-generated content, underlining the need for improved media literacy and awareness initiatives. The thematic analysis of the respondent's opinions on the ethical implications of AI-generated content underscored concerns about misinformation, bias, and a perceived lack of human essence. The study connects these findings with the TAM and Framing Theory, suggesting that perceived usefulness and the framing of AI-generated content significantly impact user trust and acceptance.

This research contributes to the ongoing discourse on AI in media and communications, underlining the need for a more nuanced understanding and responsible AI ecosystem development. It highlights the crucial role of public perception, awareness, and ethical considerations in shaping the future of AI-generated content on social media platforms