  In microblogging, hashtags are used to be topical markers, and they are
adopted by users that contribute similar content or express a related idea.
However, hashtags are created in a free style and there is no domain category
information about them, which make users hard to get access to organized
hashtag presentation. In this paper, we propose an approach that classifies
hashtags with news categories, and then carry out a domain-sensitive popularity
ranking to get hot hashtags in each domain. The proposed approach first trains
a domain classification model with news content and news category information,
then detects microblogs related to a hashtag to be its representative text,
based on which we can classify this hashtag with a domain. Finally, we
calculate the domain-sensitive popularity of each hashtag with multiple
factors, to get most hotly discussed hashtags in each domain. Preliminary
experimental results on a dataset from Sina Weibo, one of the largest Chinese
microblogging websites, show usefulness of the proposed approach on describing
hashtags.
