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论文编号：	12339
作者编号：	2120183115
上传时间：	2021/6/7 16:42:00
中文题目：	虚拟学术社区知识交流效果评价研究
英文题目：	Evaluation of knowledge exchange effect in virtual academic community
指导老师：	李旭光
中文关键字：	虚拟学术社区；知识交流；效果评价；层次分析法；模糊综合评价
英文关键字：	Virtual academic community; Knowledge exchange; Effect evaluation; Analytic hierarchy process; Fuzzy comprehensive evaluation
中文摘要：	摘要 新冠肺炎疫情爆发以来，线下的学术交流活动受到限制，在虚拟学术社区中进行学术交流成为学者更广泛的选择。相较于基于社交平台的学术交流的活跃程度，科学网等传统网站的用户规模和活跃度都明显下滑。基于此背景本文对虚拟学术社区的知识交流效果展开研究。 本文通过对虚拟学术社区知识交流相关文献的梳理，对虚拟学术社区的概念进行界定，总结归纳了虚拟学术社区知识交流的三种主要方式，并将现有的评价方法和评价指标进行分类整理。在此基础上，初步构建了虚拟学术社区知识交流效果评价指标体系。其中，一级指标三个，分别为知识交流主体、知识交流客体和知识交流环境；二级指标八个，分别为知识接收、知识提供、知识传播、知识数量、知识质量、知识时序、社区内部氛围和社区外部评价；三级指标十九个，分别为知识获取、知识应用、知识反馈、自我实现、收益获取、声望获取、知识内容多样性、知识内容完整性、知识内容可靠性、知识内容学术性、知识更新频率、知识交流周期、社区活跃度、社区友好度、社区管理、竞争优势和外界评价。 本文采用层次分析法确定指标权重，邀请领域内研究专家、学者、学术社区核心用户和社区管理者对指标重要程度进行两两比较，依据专家打分情况构建判断矩阵，计算各级指标权重，并进行一致性检验，确定各级指标权重后汇总形成综合权重。其中知识获取、知识内容可靠性、自我实现、社区内传播和社区活跃度五个指标的权重超过平均值，是提高社区知识交流效果的关键因素。 完成评价指标体系的构建后，本文分别以豆瓣人文社科类学术性小组和知乎社会学、历史学话题为实证研究对象，以目标性抽样的方式完成数据收集，采用模糊综合评价对其知识交流效果进行评价和对比分析。计算得出豆瓣社区的得分为65.77分，知乎社区的得分为66.63分，并在各级指标维度上对比二者之间的差异。 最后，在上述研究结果的支持下提出提高虚拟学术社区知识交流效果的相关建议。
英文摘要：	Abstract Since the outbreak of COVID-19, offline academic exchanges have been limited, and academic exchanges in virtual academic communities have become a more extensive choice for scholars.Compared with the academic exchange activity of social platform, the user scale and activity of traditional websites such as Science Net have decreased significantly.Based on this background, this paper studies the effect of knowledge exchange in virtual academic community. This paper defines the concept of virtual academic community by sorting out relevant literature on knowledge exchange in virtual academic community, summarizes three main ways of knowledge exchange in virtual academic community, and classifies the existing evaluation methods and evaluation indicators.On this basis, the evaluation index system of knowledge exchange effect in virtual academic community is preliminarily constructed.Among them, there are three first-level indicators, namely the subject of knowledge exchange, the object of knowledge exchange and the environment of knowledge exchange.There are eight secondary indicators, namely, knowledge reception, knowledge provision, knowledge dissemination, knowledge quantity, knowledge quality, knowledge timing, community internal atmosphere and community external evaluation.Level 3 indicators 19, knowledge acquisition, knowledge application and knowledge feedback respectively, self-realization, generating revenue, reputation knowledge acquisition, knowledge content, diversity, content integrity, knowledge content, knowledge content, academic reliability, knowledge update frequency, cycle of knowledge exchange, active, friendly community, community management evaluation, competitive advantage, and the outside world. This article uses the analytic hierarchy process to determine index weight, invite the experts and scholars, the academic community area core users and community managers to compare two index importance, construction of judgment matrix based on expert scoring, all levels of index weight calculation, and consistency inspection, determine the index weight at all levels after the summary form synthesis weights.Among them, the weight of knowledge acquisition, knowledge content reliability, self-realization, communication within the community and community activity is higher than the average, which is the key factor to improve the effect of community knowledge communication. After completing the construction of the evaluation index system, this paper takes the academic group of humanities and social sciences of Douban and the topics of sociology and history of Zhihu as the empirical research objects, completes the data collection by means of selective sampling, and evaluates and compares the effect of knowledge exchange by using fuzzy comprehensive evaluation.The score of Douban community is 65.77 points and Zhihu community is 66.63 points, and the differences between the two are compared in all levels of indicators. Finally, with the support of the above research results, relevant suggestions are put forward to improve the effect of knowledge exchange in virtual academic communities.
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