Robots are able to influence the usage of human language even after the interaction between the human and robot has ended. Humans influence each other in the usage of words, and hence, the robots they program indirectly affect the development of our society’s vocabulary. Most human–robot interaction studies focus on one robot interacting with one human. Studying the dynamic development of language in a group of humans and robots is difficult and requires considerable resource. We therefore conducted a social simulation of a human–robot communication network based on a real-world human–human network, allowing us to study how the centrality of the robots’ owners influences the propagation of words in the network and what influence the number of robots in the network has on achieving a fixation state. Our results show that robots owned by highly connected people have less effect on the dynamics of language than robots owned by less connected people. Highly connected people interact with many others and therefore are more strongly influenced by a greater number of people and their robots. We have found that 11% of the humans owning a robot is sufficient for the robots to dominate the development of the language resulting in 95% of the humans using or adopting their words.