We investigate the uses of fuck in digital social networks from social media, Twitter/X in this case. Social media outlets have so far been predominantly treated as massive text collections, but they can be effectively used to investigate the role of social networks in shaping human communication. We use user-generated texts from 5,660 social networks (with 435,345 users and 7.8 billion words) from three settings (UK, US, and Australia). With embedded network information, this massive dataset enables us to investigate how network properties, that of the size and the strength of the network, influence the use of offensive words in these three settings. Our findings show that Americans use fuck most frequently, while Australians least frequently but they are highly creative with spelling variants of the word. Contrary to prior studies, we observe that people on this social media application swear more with acquaintances than with friends, but only in smaller networks − in larger networks of >100 people, the differences level out. Overall, this study highlights the benefits of using social media data that can be enriched to allow access to the social networks that people interact in.