  Addressing collective issues in social development requires a high level of
social cohesion, characterized by cooperation and close social connections.
However, social cohesion is challenged by selfish, greedy individuals. With the
advancement of artificial intelligence (AI), the dynamics of human-machine
hybrid interactions introduce new complexities in fostering social cohesion.
This study explores the impact of simple bots on social cohesion from the
perspective of human-machine hybrid populations within network. By
investigating collective self-organizing movement during migration, results
indicate that cooperative bots can promote cooperation, facilitate individual
aggregation, and thereby enhance social cohesion. The random exploration
movement of bots can break the frozen state of greedy population, help to
separate defectors in cooperative clusters, and promote the establishment of
cooperative clusters. However, the presence of defective bots can weaken social
cohesion, underscoring the importance of carefully designing bot behavior. Our
research reveals the potential of bots in guiding social self-organization and
provides insights for enhancing social cohesion in the era of human-machine
interaction within social networks.
