This application discloses an AI-based multi-user science popularization knowledge
interaction method and
system, relating to the field of intelligent question-answering technology. The method includes: acquiring historical input content from all users in a
discussion group to construct a semantic graph; identifying
consensus patterns by scanning the semantic graph and generating
consensus proposals for each pattern; pushing the
consensus proposals to all users in the
discussion group for consensus feedback operations and determining the status of the consensus proposals;
parsing real-time input content to detect whether there is a conflict between the input content and active consensus; if a conflict exists, determining the conflict pattern, confirming the conflict confidence level, and generating an early warning; evaluating the input content through a deviation analyzer to calculate the deviation concentration and
diffusion rate; triggering a risk warning when the deviation concentration exceeds a deviation concentration threshold and the
diffusion rate exceeds a
diffusion rate threshold, scheduling an AI role model as a virtual participant to publish guiding content for corrective intervention, and calculating a correction effect index.