Sciweavers

ECIR
2016
Springer

LExL: A Learning Approach for Local Expert Discovery on Twitter

8 years 7 months ago
LExL: A Learning Approach for Local Expert Discovery on Twitter
Abstract. 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 candidate’s 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.
Wei Niu, Zhijiao Liu, James Caverlee
Added 02 Apr 2016
Updated 02 Apr 2016
Type Journal
Year 2016
Where ECIR
Authors Wei Niu, Zhijiao Liu, James Caverlee
Comments (0)