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Shanfan Zhang

dblp:315/2579 · DBLP profile ↗
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4ranked-venue papers
2as first author
4since 2021 · last 2026
0000-0001-6900-8586ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 first-author · 3 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%
Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%
Artificial intelligence
1 paper
Multi-agent systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational social science and digital humanities
opinion dynamics
1.012026
Game Theory Based Community-Aware Opinion Dynamics · AAAI 2026
Algorithmic game theory and mechanism design
network games
1.012026
Game Theory Based Community-Aware Opinion Dynamics · AAAI 2026
Knowledge, reasoning and agents › Multi-agent systems › agent-based simulation › social simulation
agent-based social simulation
0.312026
Game Theory Based Community-Aware Opinion Dynamics · AAAI 2026

Methods — techniques the papers use, named apart from their topics

non-cooperative game · 3.0co-evolutionary framework · 3.0bounded-confidence model · 3.0
YearPublicationVenuePosition
2026 Game Theory Based Community-Aware Opinion Dynamics
abstract
Understanding opinion evolution in complex social networks is crucial for modeling social influence and predicting collective behavior. Yet, most models overlook how community structures shape opinion updates, often assuming homogeneous influence. This abstraction neglects individuals’ stronger responsiveness to intra-community peers—an empirically observed driver of localized consensus and inter-group polarization. We propose GCAOFP, a co-evolutionary framework that jointly models opinion dynamics and community formation as an integrated process. In GCAOFP, agents strategically alternate between two coupled modules: (1) a Community Dynamics Module, where agents play a non-cooperative game to optimize community memberships based on opinion alignment and structural cohesion; and (2) an Opinion Adjustment Module, where agents revise opinions via a bounded-confidence mechanism modulated by community-induced influence weights. This dual-stage process captures the feedback loop between structure and opinion. We prove that GCAOFP converges to stable equilibria, ensuring intra-community consensus and inter-community diversity—dynamics that standard models fail to replicate. Experiments on real-world networks show that GCAOFP better reproduces localized opinion clusters, while offering strong scalability and interpretability, illuminating the strategic foundations of polarization.
Shanfan Zhang, Yongyi Lin, Xiaoting Shen, Zhan Bu
AAAI1
2024 ClusterLP: A novel Cluster-aware Link Prediction model in undirected and directed graphs
Shanfan Zhang, Wenjiao Zhang, Zhan Bu
Int. J. Approx. Reason.1
2023 Community-aware empathetic social choice for social network group decision making
Zhan Bu, Shanfan Zhang, Shanshan Cao, Jiuchuan Jiang, Yichuan Jiang
Inf. Sci.2
2022 Link prediction based on higher-order structure extraction and autoencoder learning in directed networks
Shanfan Zhang, Zhan Bu, Jinwei Du, Changjian Fang
Knowl. Based Syst.2