科研社交网络中用户社会资本对知识共享影响的实证研究

发布时间：2018-05-14 04:30

本文选题：科研社交网络 + 社会资本　；参考：《合肥工业大学》2017年硕士论文

【摘要】：Web 2.0时代,在“互联网+”浪潮的带动下,科研社交网络作为知识共享的密集平台,越来越受到学者们的关注。我国的科研社交网站还处于起步阶段,相较于国外成熟的科研社交网站仍存在一些问题和不足。本文以科学网中管理专业用户为研究对象,以互动关系、个体中心性、信任、共同语言和共同愿景来考察用户在科研社交网络中的社会资本三个维度,同时选择使用知识共享的数量和质量来评价用户的知识共享情况,在此基础上构建模型实证探究科研社交网络中用户社会资本对知识共享的影响。通过采用网页爬虫技术自编程序,爬取了科学网中管理专业2163个用户数据,并利用用户的好友关系建立网络,使用R软件中的“igraph”包计算出个体中心性的相关指标。经过数据预处理和筛选,最终获得科学网管理专业439个用户的样本数据,并以上文七个研究变量为出发点,通过相关性分析、回归分析和单因素方差分析得到实证研结果:个体中心性对知识共享数量存在显著正向作用;互动关系、个体中心性、信任和共同语言对知识共享质量存在显著正向作用;互动关系、信任、共同语言和共同愿景对知识共享的数量不存在显著影响;共同愿景对知识共享质量也不存在显著影响;管理专业二级学科的不同会引起信任差异;教育程度不会引起本文各研究变量的显著差异;职称的不同会引起信任差异;博主身份的不同会引起个体中心性、信任、共同语言和知识共享质量的差异。
[Abstract]:In the era of Web 2.0, driven by the tide of "Internet", the scientific research social network as a dense platform for knowledge sharing has been paid more and more attention by scholars. The scientific research social network in our country is still in its infancy, and there are still some problems and shortcomings compared with the mature scientific research social network in foreign countries. This paper takes the professional users of management in ScienceNet as the research object, and examines the three dimensions of social capital of users in the social network of scientific research in terms of interaction, individual centrality, trust, common language and common vision. At the same time, we choose to use the quantity and quality of knowledge sharing to evaluate the knowledge sharing of users, and then build a model to explore the impact of social capital of users on knowledge sharing in scientific research social networks. By using the web crawler technique, 2163 users' data of management specialty in the scientific network were crawled, and the network was established by using the user's friend relationship, and the relevant index of individual centrality was calculated by using the "igraph" package in R software. After data preprocessing and screening, the sample data of 439 users of the science network management specialty were obtained, and based on the seven research variables above, the correlation analysis was carried out. Regression analysis and univariate ANOVA show that: individual centrality has a significant positive effect on the quantity of knowledge sharing, interaction, individual centrality, trust and common language have significant positive effects on the quality of knowledge sharing. Interaction, trust, common language and common vision have no significant influence on the quantity of knowledge sharing, shared vision has no significant influence on the quality of knowledge sharing, the difference of management subject will cause the difference of trust. Education level will not lead to significant differences in the study variables; different titles will lead to differences in trust; different identities of bloggers will lead to individual centrality, trust, common language and knowledge sharing quality differences.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.09;G203

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