This research investigates implicit hostility, threats, and miscommunication in online interactions, where offensive intent is often subtle and context-dependent. Due to the difficulty of obtaining labeled user- generated data, the study explores methods to identify and analyze implicit emotional cues using limited seed information. By leveraging advanced retrieval and generative approaches, the research aims to alleviate communication breakdowns and prevent misused language from escalating conflicts. The findings will contribute to better content moderation, improved sentiment analysis, and enhanced digital discourse understanding in social and professional communication platforms.