摘要：

Abstract:

【Purpose/significance】Users have different needs for health information and form different interest groups. The discovery

of user interest groups and the analysis of their constituent organizations will help to explore the relevant laws of knowledge transfer

and diffusion in online health communities.【Method/process】This study uses ATM model to identify user preference topics through

text clustering, introduces user mapping table and Hellinger distance algorithm, identifies user interest groups, and analyzes the struc⁃

ture and preference content of user interest groups. At the same time, the yx129.com website was used as a case to further identify and

analyze the user interest groups of the healthy community and their related characteristics.【Result/conclusion】the gout community of

yx129.com website can be divided into three preference themes: health care, symptoms and treatment. On the basis of this, combined

with the user interest group structure analysis and the specific content of preference theme. It is found that the scale of different inter⁃

est groups is different, the composition structure has certain cross-cutting, and to some extent, according to the stage characteristics of

disease development, there is dynamic mobility.【Innovation/limitation】Based on the topic user mapping relationship, this paper ex⁃

plores the distribution of user groups with similar preferences and topic preferences in online health community, In the future, we need

to further improve the ability of the model to deal with unbalanced text in the future.