We argue that more effort should be put in making state-of-the-art results from network science actionable by those trained as qualitative researchers. Our contribution, which targets the analysis of socio-semantic networks, has been to develop an extensive methodology in tandem with different groups engaged in field research, incorporating recent advances in community detection and higher-order graphs by means of specially crafted interfaces for graph data and their model representations. The computational tools of this approach — nicknamed sashimi — are appropriately available as a suite of no-code methods in a gratis cloud service, and also as a free-and-open-source software library. We present results from the latest research projects experimenting with the approach: (a) in the field of Transition Studies, an investigation into the variety of disciplinary manifestations throughout the social sciences of the "research problem of destabilisation of socio-technical systems", that seeks to inform current destabilisation/discontinuation/phase-out scholarship with a wider understanding of the problem; (b) in Science and Technology Studies, an analysis of policy documents pertaining to the regulation of artificial intelligence, identifying the interplay between actors associated with different themes, sectors and perspectives (solutionism, contestation, regulation); (c) still in STS, an analysis of social media interactions concerning environmental controversies, focusing on the issue of pesticides. In the context of these examples, we'll explain a set of concepts and practices, emerging from our usage, to productively co-construct meaning between the representations exposed through the interfaces, and the goals, inputs and choices of a researcher with field and experiential knowledge. In particular, how to interpret the clusters and the specificity and commonality scores of inter-cluster relationships employed in the maps, how to formulate inquiries based on sequences of network filtering and dimension chaining operations, and finally how to construct coherent groups of document clusters we call constellations, and identify attribute flows in their cores and frontiers.