The mapping of scientific fields, based on principles established in the seventies, has recently known a remarkable development and applications are now booming with progress in computing efficiency. We examine here the convergence of two thematic mapping approaches, citation-based and word-based. Both approaches are classical commonly used in information science and their comparison and combination appeal since they rely on quite different sociological backgrounds. The same literature in the nano-science field was broken down into research themes, using the same clustering technique on the two networks separately. The tool for comparison is the table of intersections of the M clusters (here M=50) built on either side. A classical visual exploitation of such contingency tables is based on correspondence analysis. We will investigate another type of representation: the rearrangement of the intersection table (block-modeling), resulting in pseudo-map. The interest of this representation for confronting the two breakdowns is discussed. The result achieved on the nano-sciences literature proves the pretty strong agreement between the citation-based and term-based representations. The amount of convergence found is, in our view, a strong argument in favor of the reliability of bibliometric mapping. However the outcomes are not convergent at the degree where they can be substituted to each other. Differences highlight the complementarity between approaches based on different networks. In contrast with the strong informetric posture found in recent literature, where lexical and citation markers are considered as miscible tokens, the framework proposed here does not mix the two elements at an early stage, in compliance with their contrasted logic.