<![CDATA[In the rapidly evolving landscape of social media, effective communication adaptation is crucial for enhancing user interaction and engagement. This study explores the role of AI-based decision support systems in innovating how social media users adapt their communication styles to diverse contexts and audiences. Leveraging intelligent algorithms, the research investigates mechanisms that enable dynamic analysis and personalized recommendations to improve message clarity, relevance, and impact. By integrating data riven insights and machine learning models, the system supports users in crafting adaptive and persuasive communication strategies that resonate with their network. The findings highlight the potential of combining expert systems with advanced computational techniques to facilitate real-time decision making in social interactions online. This approach not only enhances the quality of communication but also fosters more meaningful connections across heterogeneous user groups. The study contributes practical implications for developers and practitioners aiming to design intelligent platforms that empower social media users with innovative tools for communication adaptation, ultimately driving more effective and engaging digital experiences.]]>
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