In navigating the challenges of real-time semantic communication (SC) codec updates in the 6G-era non-terrestrial network (NTN)-assisted vehicular networks (NTN-VNs), a crucial component of intelligent transportation systems (ITS), this article introduces a novel approach inspired by human society. Facing complexities like 3-dimensional updating, network dynamism, and updating costs, NTN-VNs are treated as social networks. The proposed NTN-VN federated learning (NTN-VN-FL) framework asynchronously addresses challenges such as uplink and downlink SC codec updates, device decentralization, and asynchronous updating. By viewing device behaviors during updating as social behaviors with economic costs, an NTN-VN social management system ensures the proper functioning of the social network in the context of NTN-VN-FL. An economical social behavior selection mechanism, based on the reverse auction game for NTN-VN-FL, minimizes training delay and device energy costs, considering social relationships. The article also presents a two-stage Stackelberg game with the Vickrey auction rule to maximize social welfare in the auction. Simulation results highlight the superiority of NTN-VN-FL over existing potential application algorithms, effectively addressing the unique challenges of SC codec updating in NTN-VN. The efficacy of the social management system and social behavior selection mechanism is demonstrated in achieving optimal outcomes.