【Purpose/significance】Based on the information ecology perspective, this paper explores how the variables of information,

information people, information environment and information technology play a role in the process of public opinion information dis⁃semination of hot events in social media , and further studies the influencing factors and trigger mechanism of hot public opinion dis⁃semination of hot events.【Method/process】Following the research logic of raising questions, establishing hypotheses and constructing research models, this paper uses the questionnaire survey method to obtain 1970 valid samples, analyzes the variables which can affect the information dissemination of hot events and the influencing process, and then empirically verifies the research models proposed.【Result/conclusion】 It is found that factors such as the implicit characteristics of information, users' degree of rationality, users' psy⁃chology of empathy for information content, users' assessment of the acquisition of individual benefits, and the opinion environment formed due to social relationships have significant effects on the spread of hot public opinions. Among them, the implicit characteris⁃tics of hot public opinion information can trigger users' empathy psychology, which is an important factor to trigger the dissemination of public opinion information, and the empathy psychology will positively influence users' public opinion dissemination behavior.When the number of social relationships of users is within a certain range, the more the number of social relationships, the greater the possibility of users spreading public opinion information. Users' rational judgment of hot public opinion will negatively influence the spreading behavior. When spreading information is beneficial to social media persona, it will promote users' spreading behavior.【Inno⁃vation/limitation】 The influencing factors that trigger the spread of hot public opinions and their mechanism processes are unearthed.In the subsequent study, the scope of the trigger factors will be expanded to further improve the trigger mechanism model.