Social network services (SNSs) are examples of non-living systems that evolve in response to internal and external events and have many similar characteristics assumed in biological evolution. In the present study, we analyzed the evolution of hashtag use on an SNS called RoomClip. Using a biological evolution analogy, we viewed each post (photo submission) as a species and each set of associated hashtags with a photo as genome. Further, we virtually defined parent–offspring relationships among posts based on their hashtag use and observed the resulting family tree of posts. Our analysis revealed that there was weak selection on hashtag usages relative to the Yule–Simon processes with strong feedback, and hashtag use quickly diverged. The evolution of novel hashtag combinations was observed, which is more salient than an evolution of individual novel hashtags.