Monitoring, governing, and guiding public opinion on social media during emergencies is challenging, often leading to mass panic, rumors, and public opinion crises. Understanding the scale evolution of information and subjects within the public opinion ecology of emergencies can aid in achieving macrocontrol. To address this, an information‐subject dual‐structure model was developed to illustrate the scale development trend. Fitting and prediction methods based on the model were proposed, and general rules were provided through simulation. For empirical research, data from three categories of six emergency events were downloaded from the GsData platform. The linear regression method was used to predict the trend of subjects and information, achieving an F 1 fit above 82% for the six datasets. Subsequently, a fine‐tuning matrix was established, increasing the F 1 values to over 98.30%, thereby confirming the model’s interpretability and universality.
Xia et al. (Thu,) studied this question.