Subjects: Library Science，Information Science >> Library Science submitted time 2023-08-27 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Although previous studies have examine the influencing factors of users' information-seeking in social Q&A communities, current knowledge about the impact of the configurations of these factors on users' information-seeking is limited.[Method/process] To fill this gap, this study uses a mixed methods combining the regression analysis and qualitative comparative analysis (QCA) to explore the configurations of the factors that exert a profound effect on users' information-seeking in social Q&A communities.[Result/conclusion] This study show that the findings from the analysis by using regression analysis contribute to exploring what factors may affect users' information-seeking; whereas the findings from the analysis by using QCA contribute to understanding the configurations of these influencing factors of users' information-seeking.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-07-26 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Based on the current situation of low response rate of social Q&A communities, the research can provide references for social Q&A communities to improve user activation, retention rate and user experience by predicting the response rate of questions.[Method/process] The paper took "Baidu Know" as the research platform, and grabbed 10 640 question records under 14 topics set by the platform. From the perspective of question and questioner characteristics, the paper constructed the research framework of the factors affecting the question response rate. The binary logistic regression was used to verify the influencing factors, and then the prediction model of the question response rate was constructed.[Result/conclusion] The prediction research of response rate in social Q&A communities can improve the quality of platform information services and promote user knowledge contribution behavior. The experimental results have verified the validity of the model in the prediction of question response rate of the social Q&A communities.
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