<![CDATA[This study analyzes public perception and knowledge regarding rip current hazards at Drini Beach, Gunungkidul, Yogyakarta, using X (Twitter) data collected between January 1 and April 22, 2025. The research was motivated by the low level of public awareness, which contributes to recurring coastal accidents. Data were obtained through a Python-based crawling process in Google Collaboratory using the hashtags #ripcurrent and #pantaidrini, producing 200 tweets, of which 23 were identified as relevant after a filtering stage. These tweets were further examined using Social Network Analysis (SNA) to identify key actors, interaction patterns, and information dissemination networks. Complementary spatial analysis was performed through the interpretation of Google Earth imagery to identify rip current–prone zones and relate them to public responses on social media. The findings indicate a sharp increase in online discussion and awareness following a fatal incident involving a student from Mojokerto in January 2025. Although limited in number, relevant tweets effectively disseminated safety information and risk awareness. This study highlights the potential of X as a rapid disaster communication tool and its value in enhancing community preparedness in coastal tourism areas.]]>
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