A topic trend on p2p based social media

Abstract

This paper shows a topic trend on a P2P based Social Network Service. There is a text-based Social Network Service (SNS) named Mastodon. Mastodon is a peer-to-peer and open-source SNS. Many persons and companies run Mastodon instances. We consider that there is a topic trend for each node. In this paper, we collect text messages and infer topic trend on a Mastodon instance using Latent Dirichlet Allocation(LDA). The understanding a topic trend helps to choice an instance that a user should participate.