In recent years, a new scientific field known as network science has been emerging. Network science is concerned with understanding the structure and properties of networks. One concept that is commonly used in describing a network is how the nodes in the network cluster together. The current research applied the idea of clustering to the study of how phonological neighbors influence visual word recognition. The results of 2 experiments converge to show that words with neighbors that are highly clustered (i.e., are closely related in terms of sound) are recognized more slowly than are those having neighbors that are less clustered. This result is explained in terms of the principles of interactive activation where the interplay between phoneme and phonological word units is affected by the neighborhood structure of the word. It is argued that neighbors in more clustered neighborhoods become more active and directly compete with the target word, thereby slowing processing.