The understanding of how science works can contribute to making scientific development more effective. In this paper, we report an analysis of the organization and the interconnection between unbalanced areas of study. More specifically, we considered two important subareas in analytical chemistry, namely capillary electrophoresis (CE) and mass spectrometry (MS). These areas are particularly interesting because MS is employed in a bigger range of applications than CE. Consequently, these different portions of papers can interfere in the quality of the searches for papers devoted to CE–MS. Here, we considered a citation network in which the nodes and connections represent papers and citations, respectively. The network clusters were detected by employing the Infomap algorithm. By considering the clusters and the respective abstracts, the subjects were identified. Interesting results were found, including a marked separation between some clusters of articles devoted to instrumentation techniques and applications, which was quantified from the abstract contents. For instance, the most well-defined community was assigned as CE (Instru.), with 73.8% of the papers having abstracts that include the word “electrophoresis” and not the word “mass”. However, the papers that describe CE–MS did not lead to a well-defined cluster. In order to better understand the organization of the citation network, we considered a multi-scale analysis, in which we used the information regarding sub-clusters. Firstly, we analyzed the sub-cluster that contains the first article devoted to the coupling between CE and MS, whose subject was found to be a good representation of its sub-cluster. The second analysis was about the sub-cluster of a seminal paper known to be the first that dealt with protein analysis by using CE–MS and a similar result was obtained. By considering the proposed methodologies, our paper can contribute to researchers working with similar scenarios, since it shows that a given subject can be spread on many clusters of the network, therefore, lead to better literature reviews.

对科学工作原理的理解可以有助于使科学发展更加有效。在本文中，我们报告了对组织和不平衡研究领域之间的相互联系的分析。更具体地说，我们考虑了分析化学中的两个重要子区域，即毛细管电泳（CE）和质谱（MS）。这些领域特别有趣，因为MS的应用范围比CE大。因此，论文的这些不同部分可能会干扰致力于CE-MS的论文的搜索质量。在这里，我们考虑了一个引文网络，其中的节点和连接分别代表论文和引文。通过使用Infomap算法检测网络群集。通过考虑聚类和相应的摘要，确定了对象。发现了有趣的结果，其中包括一些专门介绍仪器技术和应用的文章之间的明显区别，这是从抽象内容中量化的。例如，定义最明确的社区被分配为CE（仪器），其中73.8％的论文摘要包含“电泳”一词而不是“质量”一词。但是，描述CE-MS的论文并未得出明确定义的集群。为了更好地理解引文网络的组织，我们考虑了多尺度分析，其中使用了有关子集群的信息。首先，我们分析了包含第一篇文章的子集群，该文章专门讨论了CE和MS之间的耦合，发现该主题很好地代表了它的子集群。第二个分析是关于一个开创性论文的子类，该开创性论文是第一个使用CE-MS进行蛋白质分析的论文，并获得了类似的结果。通过考虑所提出的方法，我们的论文可以为研究类似场景的研究人员做出贡献，