User Association Data Mining and Group Portrait Classification of Health Anxiety in Online Medical Community
[Purpose/significance]By constructing a portrait of health anxiety users in the online medical community,we can reveal the characteristics of needs and behaviors of different types of health anxiety users,and provide a basis for accurate recommendation and personalized service of user health information.[Method/process]According to the existing research results and the characteris-tics of health anxiety user data in online medical community,the label framework is constructed.The concept lattice of health anxiety user label is constructed by formal concept analysis method,and the association rules of user characteristics are mined to realize the classification of health anxiety user groups.[Result/conclusion]According to the label characteristics of different types of health anxi-ety user groups,they are divided into four categories:over-inquiry type,positive solution type,negative escape type and edge stroke type.The key characteristics of various types of health anxiety user portraits are analyzed in detail and a more comprehensive explana-tion is provided.[Innovation/limitation]This study reveals the characteristics and association rules of different health anxiety user groups,which has certain guiding significance for guiding health anxiety users to establish a correct view of health and promoting the sustainable development of online medical community.However,the multi-source data fusion of different disease communities is not considered,and the breadth and depth of the sample coverage need to be further improved.
online health communityhealth anxietyuser portraituser tagsassociation rules
NETL
NSTL
万方数据
