Recent research in data dissemination for Vehicular Ad Hoc Networks (VANETs) focuses on enhancing the efficiency, reliability, and scalability of information sharing among vehicles in highly dynamic and dense environments. Advanced methods utilize adaptive broadcasting, clustering, and optimization-based schemes to minimize redundant transmissions and control network congestion. Machine learning and artificial intelligence techniques are increasingly integrated to predict vehicle movement patterns and improve data delivery accuracy. Moreover, hybrid dissemination strategies combining vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications have been explored to ensure timely and context-aware message propagation for safety, infotainment, and traffic management applications. These developments collectively aim to achieve low latency, high packet delivery ratios, and better utilization of network resources in next-generation intelligent transportation systems.