24 citations · 68 across the 10 of their papers we have counts for
10 papers
Inductive Dual-Polarity Modeling via Static-Dynamic Disentanglement for Dynamic Signed Networks
Yikang Hou, Junjie Huang, Yijun Ran +1
Dynamic signed networks (DSNs) are common in online platforms, where time-stamped positive and negative relations evolve over time. A core task in DSNs is dynamic edge prediction,…
A generalized motif-based Naïve Bayes model for sign prediction in complex networks
Yijun Ran, Si-Yuan Liu, Junjie Huang +2
Signed networks, encoding both positive and negative interactions, are essential for modeling complex systems in social and financial domains. Sign prediction, which infers the sig…
Identifying social bots via heterogeneous motifs based on Naïve Bayes model
Yijun Ran, Jingjing Xiao, Xiao-Ke Xu
Identifying social bots has become a critical challenge due to their significant influence on social media ecosystems. Despite advancements in detection methods, most topology-base…
Machine Learning Informed by Micro and Mesoscopic Statistical Physics Methods for Community Detection
Yijun Ran, Junfan Yi, Wei Si +2
Community detection plays a crucial role in understanding the structural organization of complex networks. Previous methods, particularly those from statistical physics, primarily…
Uncovering multi-order Popularity and Similarity Mechanisms in Link Prediction by graphlet predictors
Yong-Jian He, Yijun Ran, Zengru Di +2
Link prediction has become a critical problem in network science and has thus attracted increasing research interest. Popularity and similarity are two primary mechanisms in the fo…
The maximum capability of a topological feature in link prediction
Yijun Ran, Xiao-Ke Xu, Tao Jia
Networks offer a powerful approach to modeling complex systems by representing the underlying set of pairwise interactions. Link prediction is the task that predicts links of a net…
A novel similarity measure for mining missing links in long-path networks
Yijun Ran, Tianyu Liu, Tao Jia +1
Network information mining is the study of the network topology, which answers a large number of application-based questions towards the structural evolution and the function of a…
CasSeqGCN: Combining Network Structure and Temporal Sequence to Predict Information Cascades
Yansong Wang, Xiaomeng Wang, Radosław Michalski +2
One important task in the study of information cascade is to predict the future recipients of a message given its past spreading trajectory. While the network structure serves as t…
A generalized linear threshold model for an improved description of the spreading dynamics
Yijun Ran, Xiaomin Deng, Xiaomeng Wang +1
Many spreading processes in our real-life can be considered as a complex contagion, and the linear threshold (LT) model is often applied as a very representative model for this mec…
Measuring similarity in co-occurrence data using ego-networks
Xiaomeng Wang, Yijun Ran, Tao Jia
The co-occurrence association is widely observed in many empirical data. Mining the information in co-occurrence data is essential for advancing our understanding of systems such a…