@article{article_1903726, title={Professional Ethos in Action: Rhetorical Move Variation in Turkish C2C Vehicle Listings}, journal={Dilbilim Araştırmaları Dergisi}, volume={37}, pages={97–124}, year={2026}, DOI={10.18492/dad.1903726}, url={https://izlik.org/JA93LE97PC}, author={Bozkurt, Ferdi and Doğru, Fatih}, keywords={C2C communication, discourse, e-commerce, persuasion, professionality, rhetoric, vehicle listings}, abstract={This study investigates the interplay between professional identity and rhetorical strategies in consumer-to-consumer (C2C) vehicle advertisements on sahibinden.com, a prominent Turkish digital marketplace. Employing Swales’ (1990) move-step framework, we conduct a genre analysis of 50 professionally attributed listings to delineate occupation-based persuasive patterns. A mixed-methods approach—quantitative chi-square tests (χ² = 270.85, *p* < .001, Cramér’s V = 0.175) and qualitative scrutiny of standardized residuals—reveals statistically significant divergences in rhetorical moves across professions. Noteworthy findings include: (1) Medical professionals leverage institutional credibility (Z > +2), deploying document-backed assertions to underscore trustworthiness; (2) Mechanics favor colloquial analogies (Z > +2) and imperative directives, reflecting hands-on expertise; (3) Imams embed religious appeals (Z > +2) within closing sequences, merging moral authority with transactional discourse; and (4) Nurses disproportionately reference gender (Z ≈ +3), capitalizing on sociocultural stereotypes associating female sellers with meticulous upkeep. Dominant moves—User Information (24.6%) and Creditableness (13.9%)—underscore the centrality of epistemic and affective persuasion in C2C contexts. The study advances genre theory by illuminating how professional ethos is commodified within informal digital spaces, challenging rigid boundaries between institutional and vernacular rhetoric. Limitations, including the culturally bounded sample and unexamined gender dynamics, necessitate cross-linguistic replication. Future research should employ multivariate models to isolate confounding variables (e.g., regional dialects, platform-specific norms).}, number={1}