<![CDATA[The spread of fake news through online social networks poses global challenges, yet its dynamics in local media ecosystems — especially in peripheral regions like Ambon, Indonesia — remain understudied. This study explores the characteristics of fake news circulation in Ambon’s digital environment, its societal impacts, and the limitations of current AI-based detection approaches. Using a mixed-method design, the research analyzes fake news content on local social media platforms, conducts stakeholder interviews, and assesses the applicability of existing detection technologies in a local context. Findings reveal that fake news in Ambon often exploits cultural, religious, and political sensitivities, leading to social fragmentation and declining trust in legitimate media. Moreover, mainstream detection systems are ineffective locally due to linguistic, contextual, and infrastructural barriers. The study highlights the need for context-sensitive, community-driven detection frameworks and contributes new perspectives on misinformation governance in localized digital ecosystems]]>
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