# Link Prediction in Social Networks: the State-of-the-Art

arXiv: https://arxiv.org/abs/1411.5118 · HTML: https://mlsanity.com/paper/1411.5118/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Nov 2014.

## Built on by (most cited first, 22 of 22)

- [DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection](https://mlsanity.com/paper/2207.03579/) (2022)
- [Sampling Enclosing Subgraphs for Link Prediction](https://mlsanity.com/paper/2206.12004/) (2022)
- [A Survey on Hyperlink Prediction](https://mlsanity.com/paper/2207.02911/) (2022)
- [A Survey of Link Prediction in Temporal Networks](https://mlsanity.com/paper/2502.21185/) (2025)
- [Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning](https://mlsanity.com/paper/2405.11911/) (2024)
- [The maximum capability of a topological feature in link prediction](https://mlsanity.com/paper/2206.15101/) (2022)
- [A Preference Random Walk Algorithm for Link Prediction through Mutual Influence Nodes in Complex Networks](https://mlsanity.com/paper/2105.09494/) (2021)
- [Forecasting Financial Market Structure from Network Features using Machine Learning](https://mlsanity.com/paper/2110.11751/) (2021)
- [BERT4FCA: A Method for Bipartite Link Prediction using Formal Concept Analysis and BERT](https://mlsanity.com/paper/2402.08236/) (2024)
- [Critical Nodes Identification in Complex Networks: A Survey](https://mlsanity.com/paper/2507.06164/) (2025)
- [Higher-Order Relations Skew Link Prediction in Graphs](https://mlsanity.com/paper/2111.00271/) (2021)
- [Network-based link prediction of scientific concepts -- a Science4Cast competition entry](https://mlsanity.com/paper/2201.07978/) (2022)
- [NODDLE: Node2vec based deep learning model for link prediction](https://mlsanity.com/paper/2305.16421/) (2023)
- [Love tHy Neighbour: Remeasuring Local Structural Node Similarity in Hypergraph-Derived Networks](https://mlsanity.com/paper/2111.00256/) (2021)
- [Completing Networks by Learning Local Connection Patterns](https://mlsanity.com/paper/2204.11852/) (2022)
- [Improving Link Prediction in Social Networks Using Local and Global Features: A Clustering-based Approach](https://mlsanity.com/paper/2305.10257/) (2023)
- [Evaluating link prediction: New perspectives and recommendations](https://mlsanity.com/paper/2502.12777/) (2025)
- [BicliqueEncoder: An Efficient Method for Link Prediction in Bipartite Networks using Formal Concept Analysis and Transformer Encoder](https://mlsanity.com/paper/2503.07645/) (2025)
- [When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction](https://mlsanity.com/paper/2507.13825/) (2025)
- [Meta-learning optimizes predictions of missing links in real-world networks](https://mlsanity.com/paper/2508.09069/) (2025)
- [HyperSearch: Prediction of New Hyperedges through Unconstrained yet Efficient Search](https://mlsanity.com/paper/2510.17153/) (2025)
- [GravityGraphSAGE: Link Prediction in Directed Attributed Graphs](https://mlsanity.com/paper/2605.09408/) (2026)

## Abstract (arXiv)

In social networks, link prediction predicts missing links in current networks and new or dissolution links in future networks, is important for mining and analyzing the evolution of social networks. In the past decade, many works have been done about the link prediction in social networks. The goal of this paper is to comprehensively review, analyze and discuss the state-of-the-art of the link prediction in social networks. A systematical category for link prediction techniques and problems is presented. Then link prediction techniques and problems are analyzed and discussed. Typical applications of link prediction are also addressed. Achievements and roadmaps of some active research groups are introduced. Finally, some future challenges of the link prediction in social networks are discussed.