J. Tang

Publications
Influence

Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

Jiezhong Qiu, Yuxiao Dong, Hao Ma, J. Li, Kuansan Wang, J. Tang
Computer Science, Mathematics
WSDM
9 October 2017

In this work, we show that all of the aforementioned models with negative sampling can be unified into the matrix factorization framework with closed forms. Expand

Social influence analysis in large-scale networks

J. Tang, Jimeng Sun, C. Wang, Z. Yang
Computer Science
KDD
28 June 2009

We propose Topical Affinity Propagation (TAP) to model the topic-level social influence on large networks. Expand

RiMOM: A Dynamic Multistrategy Ontology Alignment Framework

Juan-Zi Li, J. Tang, Y. Li, Q. Luo
Computer Science
IEEE Transactions on Knowledge and Data…
1 August 2009

We propose a systematic approach to quantitatively estimate the similarity characteristics for each alignment task and propose a strategy selection method to automatically combine the matching strategies based on estimated factors. Expand

COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

Y. Zhang, J. Tang, Z. Yang, J. Pei, Philip S. Yu
Computer Science
KDD
10 August 2015

We propose COSNET (COnnecting heterogeneous Social NETworks with local and global consistency), a novel energy-based model, to address this problem. Expand

User-level sentiment analysis incorporating social networks

Chenhao Tan, Lillian Lee, J. Tang, L. Jiang, M. Zhou, P. Li
Computer Science, Physics
KDD
21 August 2011

We show that information about social relationships can be used to improve user-level sentiment analysis. Expand

Social Influence Locality for Modeling Retweeting Behaviors

J. Zhang, B. Liu, J. Tang, Ting Chen, Juan-Zi Li
Computer Science
IJCAI
3 August 2013

We study an interesting phenomenon of social influence locality in a large microblogging network, which suggests that users' behaviors are mainly influenced by close friends in their ego networks. Expand

A Unified Probabilistic Framework for Name Disambiguation in Digital Library

J. Tang, A. Fong, B. Wang, J. Zhang
Computer Science
IEEE Transactions on Knowledge and Data…
1 June 2012

We formalize the problem in a unified probabilistic framework, which incorporates both attributes and relationships, and propose a dynamic approach for estimating the number of people K. Expand

Mining structural hole spanners through information diffusion in social networks

T. Lou, J. Tang
Computer Science
WWW '13
13 May 2013

The theory of structural holes suggests that individuals would benefit from filling the "holes" (called as structural hole spanners) between people or groups that are otherwise disconnected. Expand

Detecting Community Kernels in Large Social Networks

Liaoruo Wang, T. Lou, J. Tang, J. Hopcroft
Computer Science
IEEE 11th International Conference on Data Mining
11 December 2011

We propose Greedy and We BA, two efficient algorithms for finding community kernels in large social networks. Expand

Who will follow you back?: reciprocal relationship prediction

J. Hopcroft, T. Lou, J. Tang
Computer Science
CIKM '11
24 October 2011

We study the extent to which the formation of a two-way relationship can be predicted in a dynamic social network. Expand

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