21 citations · 30 across the 9 of their papers we have counts for
9 papers
TRGCN: A Hybrid Framework for Social Network Rumor Detection
Yanqin Yan, Suiyu Zhang, Dingguo Yu +3
Accurate and efficient rumor detection is critical for information governance, particularly in the context of the rapid spread of misinformation on social networks. Traditional rum…
Learning-based Link Prediction Methods Integrating Network Topological Features and Embedding Representations
Zi-Xuan Jin, Jun-Fan Yi, Ke-Ke Shang
Link prediction, as a frontier task in complex network topology analysis, aims to infer the existence of latent links between node pairs based on observed nodes and structural info…
Economy and Geography Shape the Collective Attention of Cities
Ke-ke Shang, Jiangli Zhu, Junfan Yi +5
Complex networks are commonly used to explore human behavior. However, previous studies largely overlooked the geographical and economic factors embedded in collective attention. T…
Dynamic Object Geographic Coordinate Recognition: An Attitude-Free and Reference-Free Framework via Intrinsic Linear Algebraic Structures
Junfan Yi, Ke-ke Shang, Michael Small
The Earth, a temporal complex system, is witnessing a shift in research on its coordinate system, moving away from conventional static positioning toward embracing dynamic modeling…
Triadic Closure-Heterogeneity-Harmony GCN for Link Prediction
Ke-ke Shang, Junfan Yi, Michael Small +1
Link prediction aims to estimate the likelihood of connections between pairs of nodes in complex networks, which is beneficial to many applications from friend recommendation to me…
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…
Adaptive Similarity Function with Structural Features of Network Embedding for Missing Link Prediction
Chuanting Zhang, Ke-ke Shang, Jingping Qiao
Link prediction is a fundamental problem of data science, which usually calls for unfolding the mechanisms that govern the micro-dynamics of networks. In this regard, using feature…
A novel metric for community detection
Ke-ke Shang, Michael Small, Yan Wang +2
Research into detection of dense communities has recently attracted increasing attention within network science, various metrics for detection of such communities have been propose…
The key to the weak-ties phenomenon
Ke-ke Shang, Michael Small, Di Yin +2
The study of the weak-ties phenomenon has a long and well documented history, research into the application of this social phenomenon has recently attracted increasing attention. H…