The measurement of sense of coherence (SOC) has received attention for more than three decades. Despite the extensive use of the SOC-13, there is still a long debate regarding its psychometric properties. Recently, there was an increasing use of network modeling as a valid alternative to latent-variable modeling. This study proposes an exploratory approach to the structure of the SOC-13 by adopting a network perspective. Network structure was estimated with Gaussian Graphical Model and Exploratory Graph Analysis (EGA) was used for inspecting network dimensionality. We fit and compared unidimensional, first and secondorder confirmatory factor analysis (CFA), Bifactor-CFA, and structure derived from EGA.Our results showed unacceptable fit values for CFA models, suggesting that SOC is not unidimensional, and that comprehensibility, manageability, and meaningfulness could not be extracted from data. The inspection of the estimated network suggested that the SOC-13 items emerged as a dynamic system of mutually interacting nodes that clustered in three distinct communities that are not those defined in the literature. EGA identified three communities of items where the first community was characterized by comprehensibility and manageability items, the second community was characterized by comprehensibility and manageability items, and the third dimension was characterized by all the meaningfulness items and one comprehensibility item.Our study presented a novel perspective in investigating the SOC-13's structure that strengthens the assumption that SOC should be conceptualized as a complex system of cognitive (comprehensibility), behavioral (manageability) and motivational dimensions (meaningfulness) that are deeply linked and not necessarily distinct.