The User Behaviors Of Government New Media

Government New Media has become a crucial component of government public service,there is a huge management and science value behind billions of user behavior records.Accurate understanding regarding user behavior expressed via Government New Media can be extremely helpful for government to have a proper usage of new media technology to meet citizen's request of public service,provide an open channel for them to express personal willing,so to realize citizen-oriented social governance.Majority of existing user behaviors analysis of government New Media focus on general information management related behaviors segmentation from the point of government didn't give full consideration to treat the Government New Media as channel to provide public service,which means still lack of the user behavior analysis from the point of public affairs user engagement.Therefore,this article,based on the theory of new public service,use a new angle do the user behavior analysis on how to provide public service,how to improve user engagement and willingness of continuous usage.The Research mainly includes the follow areas:1.Based on current status of government new media user engagement,Douser segmentation through K-means clustering analysis has split the user into type of positive,potential and expanded.From the point of political property of Government New Media behavior,introduce the CVM model,doing analysis on what are the main factors to have impact on user engagement(including apparent and invisible factors),including interesting in politics,trust on the government,engagement experience and mobilization,etc…majority of them have positive impact to the user engagement.However,apparent behaviors v.s.invisible behaviors of “trust on government” has totally opposite impact.All these researches can provide Theory foundation to how can government new media attract user engagement and how to improve user engagement performance.2.Used KANO model to do content segmentation based on user request on information,system,service and interaction.Based on calculated satisfactory improvement after fulfilling the request,content can be segmented into: mandatory request,expectation request,charming request and undifferentiated request.This article has also raise the improvement suggestion on how to measure cust satisfactory: Government New Media user satisfactory measurement table differentiate by user request.The research will further provide scientific theory on how to improve government new media user satisfactory and user experience.3.By real time internet data capture,statistical analysis,model learning,this article learns how users spread the government affairs related information,which can help with the analysis on what will impact the hot government affairs related information.Structure and features of citizens social activity related big data shows that,negative emotions\social security\information with extended reading experience can all help with the message spreading.Content,user forward behaviors,government affairs public account features all have impact on public affairs information spread.