# A Graph Convolutional Neural Network based Framework for Estimating Future Citations Count of Research Articles

arXiv: https://arxiv.org/abs/2104.04939 · HTML: https://mlsanity.com/paper/2104.04939/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 39 references that are in the map.
- First posted on arXiv 11 Apr 2021.

## Builds on (most cited first, 11 of 11)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [XGBoost: A Scalable Tree Boosting System](https://mlsanity.com/paper/1603.02754/) (2016)
- [Neural Message Passing for Quantum Chemistry](https://mlsanity.com/paper/1704.01212/) (2017)
- [Predicting citation counts based on deep neural network learning techniques](https://mlsanity.com/paper/1809.04365/) (2018)
- [Supervised Community Detection with Line Graph Neural Networks](https://mlsanity.com/paper/1705.08415/) (2017)
- [Predicting Scientific Success Based on Coauthorship Networks](https://mlsanity.com/paper/1402.7268/) (2014)
- [Predicting the Citations of Scholarly Paper](https://mlsanity.com/paper/2008.05013/) (2020)
- [Could scientists use Altmetric.com scores to predict longer term citation counts?](https://mlsanity.com/paper/1801.10311/) (2018)
- [Can Scientific Impact Be Predicted?](https://mlsanity.com/paper/1606.05905/) (2016)
- [Understanding the Impact of Early Citers on Long-Term Scientific Impact](https://mlsanity.com/paper/1705.03178/) (2017)

## Abstract (arXiv)

Scientific publications play a vital role in the career of a researcher. However, some articles become more popular than others among the research community and subsequently drive future research directions. One of the indicative signs of popular articles is the number of citations an article receives. The citation count, which is also the basis with various other metrics, such as the journal impact factor score, the h-index, is an essential measure for assessing a scientific paper's quality. In this work, we proposed a Graph Convolutional Network (GCN) based framework for estimating future research publication citations for both the short-term (1-year) and long-term (for 5-years and 10-years) duration. We have tested our proposed approach over the AMiner dataset, specifically on research articles from the computer science domain, consisting of more than 0.8 million articles.