mlsanityData to 14 Oct 2026

A Survey of Signed Network Mining in Social Media

arXiv 1511.07569 ↗First posted 24 Nov 2015cs.SI cs.AI physics.soc-phcited by 26

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Abstract (arXiv)

Many real-world relations can be represented by signed networks with positive and negative links, as a result of which signed network analysis has attracted increasing attention from multiple disciplines. With the increasing prevalence of social media networks, signed network analysis has evolved from developing and measuring theories to mining tasks. In this article, we present a review of mining signed networks in the context of social media and discuss some promising research directions and new frontiers. We begin by giving basic concepts and unique properties and principles of signed networks. Then we classify and review tasks of signed network mining with representative algorithms. We also delineate some tasks that have not been extensively studied with formal definitions and also propose research directions to expand the field of signed network mining.

Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Nov 2015.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 5; 2023: 6; 2024: 8; 2025: 4; 2026: 1.

26 papers.

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  1. 2022PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphscited by 18
  2. 2024SGPT: Few-Shot Prompt Tuning for Signed Graphscited by 6
  3. 2023Correlation Clustering with Active Learning of Pairwise Similaritiescited by 5
  4. 2024Large Language Models can Achieve Social Balancecited by 5
  5. 2022Bipartite mixed membership distribution-free model. A novel model for community detection in overlapping bipartite weighted networkscited by 4
  6. 2021MUSE: Multi-faceted Attention for Signed Network Embeddingcited by 3
  7. 2024DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networkscited by 3
  8. 2021Mixed membership distribution-free modelcited by 2
  9. 2023A Signed Subgraph Encoding Approach via Linear Optimization for Link Sign Predictioncited by 2
  10. 2023Learning Disentangled Representations in Signed Directed Graphs without Social Assumptionscited by 2
  11. 2022SigGAN : Adversarial Model for Learning Signed Relationships in Networkscited by 1
  12. 2023Trustworthiness-Driven Graph Convolutional Networks for Signed Network Embeddingcited by 1
14 more
  1. 2024Information-Theoretic Active Correlation Clusteringcited by 1
  2. 2024Link Polarity Prediction from Sparse and Noisy Labels via Multiscale Social Balancecited by 1
  3. 2025An Efficient Local Search Approach for Polarized Community Discovery in Signed Networkscited by 1
  4. 2025A Method for Handling Negative Similarities in Explainable Graph Spectral Clustering of Text Documents -- Extended Versioncited by 1
  5. 2025Higher-Order Regularization Learning on Hypergraphscited by 1
  6. 2022Signed Network Embedding with Application to Simultaneous Detection of Communities and Anomaliescited by 0
  7. 2022Signed Latent Factors for Spamming Activity Detectioncited by 0
  8. 2023Defensive Alliances in Signed Networkscited by 0
  9. 2023SGA: A Graph Augmentation Method for Signed Graph Neural Networkscited by 0
  10. 2024Adversarial Robustness of Link Sign Prediction in Signed Graphscited by 0
  11. 2024Signed graphs in data sciences via communicability geometrycited by 0
  12. 2024A Survey on Signed Graph Embedding: Methods and Applicationscited by 0
  13. 2025Cold-Start Active Correlation Clusteringcited by 0
  14. 2026Peer Effects in Signed Networks: Separating Influence Through Positive and Negative Tiescited by 0