[Objective] This paper builds a Q-LDA model to identify topics of online health community, aiming to improve the quality of information generated by the LDA model, as well as its theme representation ability. [Methods] Firstly, we evaluated and weighted the online health information. Then, we constructed a Q-LDA topic mining model based on the LDA model. Finally, we examined the proposed model with real world data. [Results] The Q-LDA model yielded better results than the traditional LDA model. The efficiency of extracting topics was improved by 16%. [Limitations] We only examined the proposed model with textual data from online discussion boards on one disease. [Conclusions] Adding quality of health information to data mining could help us meet the needs of users.
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