多维度融合的文献作者亲密度计算

Calculation of Author Intimacy Based on Multi-Dimensional Fusion

为了学术成果在不同论文作者和研究团队之间便捷交流和精准推送,需建立合理有效的学术社交网络(aca‐demic social networking,ASN),本文针对目前中文学术数据库平台尚未建立成熟的、基于文献引用的作者社交网络进行社区交互问题,以CNKI(China National Knowledge Infrastructure)数据源,某大学软件工程及信息安全学科领域的教授A及有合著或引用关系的122位作者在2014-2020年的文献数据为研究对象,构建学术作者引用网络。结合学术社交的特点,对作者、论文及引用数据进行挖掘,提出合著作者(co-author)、学科主题(subject topic)、基于学科敏感度的文献引用(sensitivity-citation)和图谱社交网络(social graph)4个维度的亲密度计算方法,加权得到网络中作者间的综合亲密度值。本文通过综合亲密度值建立作者关系图谱,得到作者在网络中的亲密度水平(author_de‐gree),用亲密度水平值与发文数量相乘得到作者的网络水平(author_weight),找出图谱中相同研究水平的作者及研究团队,为学术社交网络数据推送打好基础。

To facilitate the exchange and accurate promotion of academic achievements between different academic paper authors and research teams,a reasonable and effective academic social network needs to be established.As an author network based on literature citation has not been established in current Chinese academic database platforms for community interaction,this paper uses a CNKI data source,a professor of software engineering and information security in a university,as an example.Further,the literature data of 122 scholars who are the professor A’s co-authors or with citation relationships from 2014 to 2020 was used as the research object and a citation network of academic authors constructed.Combined with the characteristics of academic social networking,the authors,papers,and citation data were mined,and four dimensions of the intimacy calculation method based on the co-author,subject topic,sensitivity citation of subject sensitivity,and social graph were used to weight the comprehensive intimacy value among the authors in the network.In the experiment,the author relationship map was established by synthesizing the intimacy value,and the author’s intimacy level in the network was obtained.The author’s network level(weight) was obtained by multiplying the intimacy value and number of published papers.The authors and research teams with the same research level in the mapped network were found,which laid a good foundation for the data promotion of the academic social network.