Enterprise architecture (EA) network analysis has been attracting researchers' attention lately. The main source of information is the structural components, including the relations among them and how they might be structurally arranged. These relations are studied to generate valuable information for EA professionals. However, to the best of our knowledge, ours is the first attempt to combine structural information with a second source of information: expert's tacit knowledge. We believe combining these sources employing two new methods - what we call cognitive-structural diagnosis analysis and attribute check analysis - can refine the expert's knowledge about the architecture. To demonstrate these methods' feasibility, we apply them with two application architecture datasets collected in two different organizations. We also offer a classification schema for enterprise architecture network analysis at the component level, our focus. Our conclusions indicate that the cognitive- structural diagnosis analysis method minimizes analysis subjectivity while validating important components and also suggesting important structural ones to be further analyzed by experts. The attribute check analysis offers further contributions by helping in the investigation of particular attributes of applications in important architectural positions.