This paper presents a novel routing algorithm, SimBet Routing, for message delivery in sparse and disconnected Mobile Ad hoc Networks (MANETs). The authors leverage social network analysis techniques, particularly the concept of small-world dynamics, to identify bridge nodes that can facilitate information exchange between disconnected nodes. The algorithm combines a node's centrality (measured using ego networks) and social similarity to the destination node to determine the best forwarding path. SimBet Routing is evaluated through simulations using real trace data from the MIT Reality Mining project, demonstrating that it achieves delivery performance comparable to Epidemic Routing while significantly reducing overhead. Additionally, SimBet Routing outperforms PROPHET Routing, especially in scenarios with low connectivity between sending and receiving nodes. The paper concludes by highlighting the potential of these forwarding metrics in distributed systems where global topology information is unavailable.This paper presents a novel routing algorithm, SimBet Routing, for message delivery in sparse and disconnected Mobile Ad hoc Networks (MANETs). The authors leverage social network analysis techniques, particularly the concept of small-world dynamics, to identify bridge nodes that can facilitate information exchange between disconnected nodes. The algorithm combines a node's centrality (measured using ego networks) and social similarity to the destination node to determine the best forwarding path. SimBet Routing is evaluated through simulations using real trace data from the MIT Reality Mining project, demonstrating that it achieves delivery performance comparable to Epidemic Routing while significantly reducing overhead. Additionally, SimBet Routing outperforms PROPHET Routing, especially in scenarios with low connectivity between sending and receiving nodes. The paper concludes by highlighting the potential of these forwarding metrics in distributed systems where global topology information is unavailable.