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论文编号：	14077
作者编号：	2120213368
上传时间：	2023/6/8 19:15:06
中文题目：	在线问答社区中用户知识采纳行为研究： 知识内容特征与用户特征的影响
英文题目：	Research on knowledge adoption behavior in online Q&A community: the impact of knowledge content characteristics and user characteristics
指导老师：	张晓飞
中文关键字：	知识采纳； 在线问答社区； 精细加工可能性模型；信息采纳理论
英文关键字：	Knowledge adoption; Online Q&A community; Elaboration Likelihood Model; Information adoption theory
中文摘要：	在线问答社区作为知识交换的平台，用户在采纳和利用知识过程中，出现供需失衡、知识迷航、搜寻和筛选知识耗费精力较大等问题，严重降低了知识资源的利用效率，亟需探究知识采纳行为的作用机制。当前研究已经分析了不同情境下社区用户的采纳行为和采纳意愿的影响因素，包括内容特征和用户特征等多方面，然而仍存在特征度量不统一、研究结论分歧、专业视角分析不聚焦等不足。本研究基于精细加工可能性模型和信息采纳采纳理论，分析知识内容特征、用户特征（包括知识提供者与接收者特征）对接收者知识采纳行为的影响和作用机制。使用Python采集Segment Fault社区的13075份IT技术问答数据，并采用logit回归进行分析。研究发现，知识内容的特征和知识提供者的特征对接收者的知识采纳行为均会产生积极的影响，接收者的专业能力只对内容特征与知识采纳的关系有负向调节作用。在知识内容特征层面，问答的相关性越高、回答的时滞性越小，接收者采纳知识的可能性就越高，回答的文本长度跟接收者的采纳行为之间呈现倒U型关系。在知识提供者的特征方面，提供者获得的他人认可越高，在社区内的知识贡献度越多，接收者采纳知识的可能性就越高。在知识接收者的特征方面接收者的专业能力负向调节时滞性与知识采纳行为的关系，专业能力高的用户对时滞性有更强的容忍度；专业能力还负向调节文本长度与采纳行为的倒U型关系，专业能力越高的接收者对文本长度的承受上限越低，需要简洁准确的答案。本研究结论可以为降低社区的认知负荷、提升知识的采纳概率、减少问答成本提供借鉴。
英文摘要：	As the platform for knowledge exchanging, online Q&A communities often encounter problems such as supply-demand imbalance, knowledge loss, and high energy consumption in searching and filtering knowledge during the process of adopting knowledge, which seriously reduces the efficiency of knowledge utilization, and it is urgent to explore the mechanism of knowledge adoption behavior. Based on the Elaboration Likelihood Model (ELM) and Information Adoption Theory, this study analyzes the influences and mechanism of knowledge content and user (including knowledge provider and receiver) characteristics on the knowledge adoption behavior of knowledge receivers. The current research has analyzed the factors of users’ adoption behavior and willingness, including content characteristics and user characteristics. However, there are still shortcomings such as inconsistent feature measurement, divergent research conclusions, and unfocused professional perspective. In this study, 13,075 IT technical questions and the answers from the Segment Fault community were crawled, and logit regression analysis was used to test the hypotheses. This study found that both the content characteristics and the characteristics of knowledge providers had a positive impact on the knowledge adoption behavior of the receiver, while the receivers’ professional competence only moderated the relationship between content characteristics and knowledge adoption. As for content characteristics, the higher Q&A relevance or the smaller the delay, the higher the possibility of the receivers to adopt the knowledge. It’s an inverted U-shaped relationship between the text length and the adoption behavior of the knowledge receivers. In terms of the characteristics of the provider, the higher the evaluation of others and the greater the knowledge contribution of the provider, the higher the possibility of the receivers adopting the knowledge. In terms of the characteristics of the receivers, professional competence negatively moderated the relationship between time delay and knowledge adoption. The results can provide suggestions for reducing the cognitive load of the community, improving the probability of knowledge adoption, and reducing the cost of Q&A.
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