LExL: A Learning Approach for Local Expert Discovery on Twitter
Additional Document Info
Springer International Publishing Switzerland 2016. In this paper, we explore a geo-spatial learning-to-rank framework for identifying local experts. Three of the key features of the proposed approach are: (i) a learning-based framework for integrating multiple factors impacting local expertise that leverages the fine-grained GPS coordinates of millions of social media users; (ii) a location-sensitive random walk that propagates crowd knowledge of a candidates expertise; and (iii) a comprehensive controlled study over AMT-labeled local experts on eight topics and in four cities. We find significant improvements of local expert finding versus two state-of-the-art alternatives.
name of conference
Advances in Information Retrieval - 38th European Conference on IR Research, ECIR 2016, Padua, Italy, March 20-23, 2016. Proceedings