Title :
Topical Influential User Analysis with Relationship Strength Estimation in Twitter
Author :
Xinyue Liu ; Hua Shen ; Fenglong Ma ; Wenxin Liang
Abstract :
Topical Influential User Analysis (TIUA) is an important technique in Twitter. Existing techniques neglected relationship strength between users, which is a crucial aspect for TIUA. For modeling relationship strength, interaction frequency between users has not been considered in previous works. In this paper, we firstly introduce a poisson regression-based latent variable model to estimate relationship strength by utilizing interaction frequency. We then propose a novel TIUA framework which uses not only retweeting relationship but also relationship strength. Experimental results show that the proposed TIUA algorithm can greatly improve the precision and relevance on finding topical influential users in Twitter.
Keywords :
regression analysis; social networking (online); stochastic processes; Poisson regression-based latent variable model; TIUA; Twitter; interaction frequency; relationship strength estimation; retweeting relationship; topical influential user analysis; Algorithm design and analysis; Analytical models; Educational institutions; Estimation; Prediction algorithms; Twitter; Relationship strength estimation; Topical influential user analysis; Twitter;
Conference_Titel :
Data Mining Workshop (ICDMW), 2014 IEEE International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4799-4275-6
DOI :
10.1109/ICDMW.2014.11