This document summarizes a study on anonymizing centralized and distributed social networks through sequential clustering. The goal is to anonymize network data split across multiple data holders without revealing links between nodes controlled by different holders. The study presents two variants of a centralized anonymization algorithm based on sequential clustering, which significantly outperforms the current leading algorithm. Secure distributed versions are also developed, representing the first study of privacy preservation in distributed social networks. Future research directions in this area are outlined.