# A modified gravity model based on network efficiency for vital nodes identification in complex networks

arXiv: https://arxiv.org/abs/2111.01526 · HTML: https://mlsanity.com/paper/2111.01526/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 71 references that are in the map.
- First posted on arXiv 12 Oct 2021.

## Builds on (most cited first, 4 of 4)

- [Collaborative Filtering Approach to Link Prediction](https://mlsanity.com/paper/2103.09907/) (2021)
- [Influence maximization by rumor spreading on correlated networks through community identification](https://mlsanity.com/paper/1705.00630/) (2017)
- [Vital Spreaders Identification in Complex Networks with Multi-Local Dimension](https://mlsanity.com/paper/1909.13646/) (2019)
- [The Fractional Preferential Attachment Scale-Free Network Model](https://mlsanity.com/paper/2005.01512/) (2020)

## Abstract (arXiv)

Vital nodes identification is an essential problem in network science. Various methods have been proposed to solve this problem. In particular, based on the gravity model, a series of improved gravity models are proposed to find vital nodes better in complex networks. However, they still have the room to be improved. In this paper, a novel and improved gravity model, which is named network efficiency gravity centrality model (NEG), integrates gravity model and network efficiency is proposed. Compared to other methods based on different gravity models, the proposed method considers the effect of the nodes on structure robustness of the network better. To solidate the superiority of the proposed method, experiments on varieties of real-world networks are carried out.