Network analysis is often considered ill-suited to fragmentarily preserved texts. However, this paper argues that fragmentation should not be treated as a deficit but as an analytical object. By modeling the processes through which texts are produced, transformed, and editorially mediated, network analysis can reveal not only what survives but also how relational structures are reshaped.

This approach is illustrated by Damascius' vita Isidori (c. 496–526), a late antique philosophical biography preserved only in Byzantine excerpts. Rather than attempting to reconstruct the lost original, this study models the extant text as a layered relational system shaped by successive acts of selection and mediation. The analysis introduces an evidential scaling system (0–3) that classifies relationships according to textual certainty: Level 0 (editorial conjecture), Level 1 (contested attribution), Level 2 (probable attribution), and Level 3 (secure attribution). To capture the coherence of the relations themselves, the model also records whether relations occur within the same fragment or are reconstructed by combining separate fragments, producing five robustness classes that distinguish between attributional certainty and transmission coherence.

A quantitative analysis of 171 nodes and 300 edges reveals that 62.46% of relations are securely attested (Level 3), while 17.94% reflect modern editorial conjecture (Level 0). Strikingly 76.74% of all relations occur within single fragments (Robustness Classes A-B), indicating that most relations survive as locally coherent relational microstructures rather than emerging through editorial recombination. Although filtering reduces network density from 0.01 (Levels 0–3) to 0.006 (Level 3 only), the polycentric structure of the network nevertheless persists.

The study shows how evidential annotation and robustness classes enable network analysis to capture the epistemic structure of fragmentary traditions. Network analysis thus becomes a tool not for reconstructing lost social realities, but for analyzing how relational knowledge is preserved and transformed across time.