Finding prophets in the blogosphere: bloggers who predicted buzzwords before they become popular

Identifying important users from social media has recently attracted much attention in information and knowledge management community. Although researchers have focused on users' knowledge levels on certain topics or influence degrees on other users in social networks, previous works have not studied users' prediction ability on future popularity. In this paper, we propose a novel approach to find important bloggers based on their buzzword prediction ability. We conduct a time-series analysis in the blogosphere considering four factors: post earliness, content similarity, entry frequency and buzzword coverage. We perform preparatory work in categorizing a blogger into knowledgeable categories, identifying past buzzwords, analyzing a buzzword's peak time content and growth period, and finally evaluate a blogger's prediction ability on a buzzword and on a category. Experimental results on real-world blog data consisting of 150 million entries from 11 million bloggers demonstrate that the proposed approach can find prophetic bloggers and outperforms others that do not take temporal features into account.