F
Feida Zhu
Researcher at Singapore Management University
Publications - 124
Citations - 3999
Feida Zhu is an academic researcher from Singapore Management University. The author has contributed to research in topics: Social network & Topic model. The author has an hindex of 33, co-authored 121 publications receiving 3456 citations. Previous affiliations of Feida Zhu include Northeastern University (China) & University of Illinois at Urbana–Champaign.
Papers
More filters
Proceedings Article
Finding Bursty Topics from Microblogs
TL;DR: A topic model that simultaneously captures two observations is proposed that helps find event-driven posts on microblogs and helps identify and filter out "personal" posts.
Proceedings ArticleDOI
HYDRA: large-scale social identity linkage via heterogeneous behavior modeling
TL;DR: HYDRA correctly identifies real user linkage across different platforms, and outperforms existing state-of-the-art algorithms by at least 20% under different settings, and 4 times better in most settings.
Proceedings ArticleDOI
CQArank: jointly model topics and expertise in community question answering
TL;DR: This work proposed Topic Expertise Model (TEM), a novel probabilistic generative model with GMM hybrid, to jointly model topics and expertise by integrating textual content model and link structure analysis, and proposed CQARank to measure user interests and expertise score under different topics.
Journal ArticleDOI
TopicSketch: Real-Time Bursty Topic Detection from Twitter
TL;DR: In this paper, a sketch-based topic model together with a set of techniques to achieve real-time detection of bursty topics in Twitter has been proposed, which can handle hundreds of millions tweets per day, which is on the same scale of the total number of daily tweets in Twitter.
Book ChapterDOI
On recommending hashtags in twitter networks
TL;DR: A novel hashtag recommendation method based on collaborative filtering is proposed and the method recommends hashtags found in the previous month's data, which suggests that most hashtags have very short life span.