科学-技术-社会研究在信息安全研究中的应用

András Nemeslaki
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引用次数: 2

摘要

我想简单回答的研究问题和问题陈述是:在信息系统及其相关的参考领域,如社会科学、管理学、决策科学延伸到心理学,围绕“信息安全”和“社会建设”这两个关键词,可以识别出什么样的模式和具体的话语?我们可以这样开始总结结论:SCOPUS域中的“信息安全”和“社会建设”提供了广泛的社会科学和相关学科领域的文献;最初的搜索结果是406篇文章,这些文章的基本书目参数(包括关键词和摘要)被下载。我根据期刊h指数、SJR第一季度至第四季度排名以及个别论文的引用次数,将样本分为五个所谓的结构簇。三篇论文被确定为最高引用和最具影响力的论文,并分别进行分析。其他集群如下:30篇论文分为CL1、高影响集群由于其高引用和h指数,122篇论文被分成这有点难度,一个成熟的集群中,由于他们的出版日期和中引用71篇论文掉进CL3,高潜力集群中,由于其高h指数和最近的外观和最后的152篇论文被聚集到CL4,主流的样本由于媒介的影响和广泛的出版日期。使用基本的文本挖掘技术对这些聚类进行分析:词计数、关键词分析、文本聚类和N-Gram分析以及一致性分析。我发现,随着信息安全学术话语的演变,集群是不同的,每个集群在用户、机构、技术和公共政策方面都对信息安全的社会建设具有独特的附加价值。最后,提出了结论和进一步研究的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Science‒Technology‒Society Studies in Information Security Research
The research question and problem statement I posed to answer simply has been: what kind of patterns and specific discourses can be identified around the keywords of “information  security” and “social construction” in information systems and its related reference fields such as social sciences, management studies, decision sciences extended to psychology. We may start summarizing the conclusions by stating that “information security” and “social construction” in the SCOPUS domain offers a wide range of literature in the social sciences and related subject areas; the initial search resulted in 406 article hits, whose basic bibliographic parameters with keywords and abstracts were downloaded. I categorized this sample according to the journals H-index, the Scimago Journal & Country Rank (SJR) Q1‒Q4 ranking and the individual papers’ citations, into five—socalled structural—clusters. Three papers were identified as the highest referenced and most influential, and analysed separately. The other were clustered as follows: 30 papers were classified into CL1, a high impact cluster due to its high citation and H-index, 122 papers were grouped into CL2, a mature cluster, due to their publishing date and medium referencing, 71 papers fell into CL3, a high potential cluster, due to their high H-index and recent appearance and, finally 152 papers were clustered into CL4, the mainstream of the sample due to their medium impact and wide spread of publishing dates. These clusters were further analysed with basic text mining techniques: word counting, key word analysis, textual clusters and N-Gram analysis, and concordance analysis. I found that clusters are different as far as the academic discourse on information security evolves, and each contain unique added value to the social construction of information security amongst users, institutions, technology and public policy. Finally, conclusion and further research opportunities are presented.
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