This paper proposes a method for detecting new concepts in social media using co-burst pattern mining technique. The new concepts are defined as correlations between unexpected words. The target social media are viewers’ comments attached to web videos and Twitter’s tweets related to the East Japan Great Earthquake that happened on Mar. 11 in 2011. Our proposed method first crawls viewers’ comments from web videos, and extracts words from them. Then it selects motive words candidates from words, and counts the occurrence numbers of tweets that include motive words candidates. To detect new concepts, it generates burst patterns based on occurrence numbers of motive words candidates over time and detects unexpected correlationsbetween motive words candidates.
