[Purpose/significance] The paper aims to build the social QA community users to generate the quality evaluation index system, achieve automatic evaluation and selection of answers to user needs, and improve the quality of the community QA community service.[Method/process] The introduction of social emotional features and user characteristics, and factor analysis and structural equation analysis are used to build an index system for evaluating the quality of user generated answers. Then, based on the GA-BP neural network model, the automatic evaluation method of the answer quality is designed. The application of the quality evaluation index system and automatic evaluation method of user generated answers is studied.[Result/conclusion] The evaluation index system consists of 5 dimensions, including the characteristics of the answer text, the characteristics of the respondent, the timeliness, the user characteristics and the social emotional characteristics. The experimental analysis shows that the method of automatic evaluation of the answer quality based on GA-BP neural network is more accurate and lower than other methods. It is feasible and effective, and can be further applied and popularized.
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