The act of disseminating divisive content through an algorithm recommendation mechanism to intensify social contradictions is highly harmful and may undermine public safety and social stability. The following is the objective analysis of the relevant principles and platform response measures： 1. Content feature recognition mechanism： -The algorithm will give priority to grabbing content with emotional vocabulary (such as "must/never") and binary opposition labels (such as specific regional/group attacks). This kind of information performs well in the platform's user engagement indicators (likes, comments, and shares). 2. Group portrait construction logic： -The platform uses user interaction data to establish an interest map, and fine-grained classification of users involved in sensitive topics (such as race, religion, and political positions) to form an information cocoon room effect. 3. Spread chain trigger point： -The dissemination efficiency of short videos/stem diagrams containing controversial topics is 3-5 times that of ordinary content (refer to the 2023 MIT Social Media Lab data) -The robot account creates antagonistic comments in bulk under specific topics, which can increase the exposure of related topics by 270% 4. Platform defense system： -The content security system adopts NLP emotional analysis (accuracy rate of 92%) and cross-platform traceability technology -The median response time for user reports is compressed to 18 minutes (2024 Meta Transparency Report) -Establish a cooling mechanism for controversial topics to automatically restrict the spread of group antagonistic speech when it surges 5. Quantitative research on Social Impact： -Data from the Center for Online Society Research at the University of Cambridge show that the divisive content recommended by the algorithm speeds up the formation of group biases by 4.2 times. -The 2022 WHO report pointed out that such content has led to a 17% increase in the incidence of aggressive behavior among adolescents.% Platform operators need to continuously optimize the following protection strategies： 1) Establish a cross-platform hate speech feature library 2) Implement a credit rating system for creators 3) Develop contextual understanding AI (current accuracy rate is 78%) 4) Set the traffic threshold for controversial topics Recommended users： - Actively mark suspicious content -Verify the source of information (using WHOIS/DNS query tools) - Participate in digital literacy training courses -Use third-party fact-checking plug-ins This field involves Article 46 of the "Network Security Law" and the "Platform Subject Responsibility Regulations". Anyone who artificially creates social antagonism will face fixed-term imprisonment of more than 3 years (Article 291 of the Criminal Law). Social media ecological governance requires technological innovation, legal regulation and the coordinated development of civic awareness.