Community detection in social networks

By Punam Bedi, Chhavi Sharma. WIREs Data Mining Knowl. Discov., 2016

420 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/7fcec364d44a8a5953bc4b362f2fc3da4f67d86b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Chuan Zhou
2. Jia Wu
3. Quan Z. Sheng
4. Shan Xue
5. Jian Yang
6. Philip S. Yu
7. Cécile Paris
8. Surya Nepal

In Molecular Biology

1. Philip S. Yu
2. Cécile Paris
3. Jia Wu
4. Surya Nepal
5. Quan Z. Sheng
6. Chuan Zhou
7. Shan Xue
8. Di Jin

In Statistical and Nonlinear Physics

1. Philip S. Yu
2. Cécile Paris
3. Jia Wu
4. Surya Nepal
5. Quan Z. Sheng
6. Chuan Zhou
7. Shan Xue
8. Di Jin

Citations in the corpus

• A Comprehensive Survey on Community Detection With Deep Learning (2021, background): “…the patterns and functions inherent to communities [36], [37], existing surveys have mainly focused on certain aspects of community detection, including specific techniques [13], [14], [38]–[41], different network types [5], [12], [42], community types [6], [7], and application scenarios [10], [43].”