<![CDATA[In the digital era, social media has become a primary source of public opinion data that can be analyzed using artificial intelligence (AI). The utilization of AI, particularly in digital content analysis, enables researchers to extract information from social media comments more efficiently than conventional methods. This study aims to explore how AI is used in digital content analysis to understand communication patterns, sentiment, and discourse development on social media. The research employs a systematic analysis based on the PRISMA approach, filtering literature from academic databases such as Scopus, Web of Science, and Google Scholar. Additionally, this study analyzes social media comments using AI-based software, such as NVivo and other NLP tools. The findings reveal that AI enhances efficiency and accuracy in sentiment analysis, reduces subjective bias, and enables deeper insights into public opinion. However, key challenges identified include dataset bias and the interpretability of AI models. Therefore, the combination of Explainable AI and a multimodal approach in the future is expected to improve the effectiveness of AI-based sentiment analysis in digital communication.]]>
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