Profession-Based Person Search in Microblogs

Abstract

We introduce the problem of searching for professionals in microblogging platforms. We describe a study of how a group of professional journalists with some common characteristics (e.g., works in a specific language, belongs to certain region, or specializes in a particular media) can be found. Starting from seed sets of different sizes, social network features and profile content features are used to find additional journalists. The results show that combining the social network features of the reciprocated mentions and a bidirectional friend/follower graph provides a signal stronger than either of them taken independently, that both social network and profile content features are useful, and that profile content features are able to find larger numbers of less prominent journalists. We apply our methods to find the Twitter accounts of British and Arab journalists.