As thermoplastic elastomers, triblock copolymers constitute an immensely important class of shape-memory soft materials due to their unique ability to form molecular networks stabilized by physical, rather than chemical, cross-links. The extent to which such networks develop in triblock and higher-order multiblock copolymers is sensitive to the formation of midblock bridges, which serve to connect neighboring microdomains. In addition to bridges, copolymer molecules can likewise form loops and dangling ends upon microphase separation or they can remain unsegregated. While prior theoretical and simulation studies have elucidated the midblock bridging fraction in triblock copolymer melts, most have only considered strongly segregated systems wherein dangling ends and unsegregated chains become relatively insignificant. In this study, simulations based on dissipative particle dynamics are performed to examine the self-assembly and networkability of moderately segregated triblock copolymers. Utilizing a density-based cluster-recognition algorithm, we demonstrate how the simulations can be analyzed to extract information about microdomain formation and permit explicit quantitation of the midblock bridging, looping, dangling, and unsegregated fractions for linear triblock copolymers varying in chain length, molecular composition, and segregation level. We show that midblock conformations can be sensitive to variations in chain length, molecular composition, and bead repulsion, and that a systematic investigation can be used to identify the onset of strong segregation where the presence of dangling and unsegregated fractions are minimal. In addition, because this clustering approach is robust, it can be used with any particle-based simulation method to quantify network formation of different morphologies for a wide range of triblock and higher-order multiblock copolymer systems.