Metadiscourse refers to those aspects of texts which can lead to the construction of writer and reader interaction. Taken this into account, this study set to investigate how men and women used metadiscourse features in social media in the English language context. Being corpus-based in nature, this study privileged a corpus of 145,213 words gathered from such social media as Facebook, Instagram, and Twitter divided by gender of male and female who wrote in English as the language of communication. For analyzing metadiscourse features, Hyland's classification (2005) was applied that divides metadiscourse features into two main categories of interactive and interactional. The results indicated that in overall both male and female corpora contained more interactional metadiscourse features than interactive. In addition, female corpus contained more metadiscourse features than male corpus. Added to this, it was found that self-mentions were the most frequent instances of metadiscourse features in both male and female corpora. Moreover, it was revealed that although male corpus had instances of code glosses, the female corpus lacked it. The results showed that there was a statistically significant difference between males and females in using metadiscourse features. The findings of this research can have useful implications in such areas as gender studies, comparative studies, corpus-based studies, and contrastive linguistics.