DOI: 10.5281/zenodo.18775800
title: Collection of datasets (Karate, Football, Dolphin, PolBook, PolBlog, Email, CiteSeer, CORA, PubMed, and DBLP) for a parallel stacked autoencoder-based method driven by semi-supervised learning for community detection in social networks

description: ·       Zachary Karate Club (Karate): This dataset, collected by Wayne Zachary in 1977, represents the social network of members in a university Karate club. Each node represents a club member, and edges denote contact or interaction between members.

·       Bottlenose Dolphin (Dolphin): This dataset represents the social interactions of 62 dolphins in New Zealand's Doubtful Sound. It is an undirected network with two main communities, where the larger group is further subdivided into smaller groups.

·       American Football (Football): The American Football dataset captures games played between 115 Division IA teams during the 2000 Fall season. Each node represents a team, and edges represent games between teams. The teams are grouped into 12 conferences, with more frequent games occurring within each conference.

·       Political Books (Polbooks):  The Polbooks dataset includes 105 nodes representing books about U.S. politics sold on Amazon around the 2004 presidential election. Edges indicate that the same customers frequently bought these books together.

·       Political Blogs (Polblogs): This dataset includes 1490 blogs about US politics, created by Adamic and Glance in 2005.  Each node represents a blog classified as either liberal or conservative. Edges represent links between blogs.

·       Email-Eu (Email): The Email-Eu dataset represents email communication trends within a large European research institution. It records email exchanges between individuals over time, providing insights into the dynamics and organization of the communication network.

·       CiteSeer: The CiteSeer dataset is a citation network of scientific publications in the field of computer science. In this graph, each node represents a research paper, and edges denote citation relationships between papers. The documents are categorized into several predefined research topics, which are commonly used as ground-truth communities for evaluating community detection algorithms. 

·       CORA: The CORA dataset consists of a citation network of scientific publications in the domain of machine learning. Nodes correspond to individual papers, while edges represent citation links between them. Each paper is assigned to one of several subject categories, which serve as ground-truth communities. 

·       PubMed: The PubMed dataset is a citation network of biomedical research papers, particularly focusing on publications related to diabetes. In this network, nodes represent scientific articles and edges correspond to citation relationships. The papers are classified into three major categories according to the type of diabetes studied, which are often treated as ground-truth communities for evaluation purposes. 

·     DBLP: The DBLP dataset is a network of academic article citations, containing information about authors, titles, and publication venues. It is commonly used for tasks such as topic modelling, influence analysis, and author clustering.

 

Network Data Statistics Karate






Nodes



34





Edges



78





Density



0.139037





Maximum degree



17





Minimum degree



1





Average degree



4





Assortativity



-0.475613





Number of triangles



135





Average number of triangles



3





Maximum number of triangles



18





Average clustering coefficient



0.570638





Fraction of closed triangles



0.255682





Maximum k-core



5





 

 

 

Network Data Statistics Dolphin






Nodes



62





Edges



159





Density



0.0840825





Maximum degree



12





Minimum degree



1





Average degree



5





Assortativity



-0.043594





Number of triangles



285





Average number of triangles



4





Maximum number of triangles



17





Average clustering coefficient



0.258958





Fraction of closed triangles



0.308776





Maximum k-core



5





 

 

 

 

 

Network Data Statistics Football






Nodes



35





Edges



118





Density



0.198319





Maximum degree



19





Minimum degree



1





Average degree



6





Assortativity



-0.176253





Number of triangles



351





Average number of triangles



10





Maximum number of triangles



53





Average clustering coefficient



0.338986





Fraction of closed triangles



0.329268





Maximum k-core



7





Lower bound of Maximum Clique



6





 

 

 

Network Data Statistics Polbook






Nodes



105





Edges



441





Density



0.0807692





Maximum degree



25





Minimum degree



2





Average degree



8





Assortativity



-0.127896





Number of triangles



1.7K





Average number of triangles



16





Maximum number of triangles



76





Average clustering coefficient



0.487527





Fraction of closed triangles



0.348403





Maximum k-core



7





 

 

 

 

 

Network Data Statistics Polblog






Nodes



1.5K





Edges



19K





Density



0.0171477





Maximum degree



467





Minimum degree



0





Average degree



25





Assortativity



-0.196103





Number of triangles



459.4K





Average number of triangles



308





Maximum number of triangles



9.5K





Average clustering coefficient



0.312823





Fraction of closed triangles



0.251111





Maximum k-core



44





Lower bound of Maximum Clique



19





 

 

 

Network Data Statistics E-Mail






Nodes



1k





Edges



25k





Density



0.00027





Maximum degree



1,383





Minimum degree



1





Average degree



10.02





Assortativity



-0.110





Number of triangles



727,044





Average number of triangles



19.82





Maximum number of triangles



5,234





Average clustering coefficient



0.497





Fraction of closed triangles



0.085





Maximum k-core



43





Lower bound of Maximum Clique



20





 

 

 

 

Network Data Statistics CiteSeer






Nodes



3.3K





Edges



4.5K





Density



0.000851796





Maximum degree



99





Minimum degree



1





Average degree



2





Assortativity



0.0480638





Number of triangles



3.5K





Average number of triangles



1





Maximum number of triangles



85





Average clustering coefficient



0.144651





Fraction of closed triangles



0.130144





Maximum k-core



8





Lower bound of Maximum Clique



6





 

 

 

Network Data Statistics CORA






Nodes



2.7K





Edges



5.4K





Density



0.0014812





Maximum degree



169





Minimum degree



1





Average degree



4





Assortativity



-0.0656162





Number of triangles



5.4K





Average number of triangles



2





Maximum number of triangles



170





Average clustering coefficient



0.246175





Fraction of closed triangles



0.0997136





Maximum k-core



6





Lower bound of Maximum Clique



5





 

 

 

 

 

Network Data Statistics PubMed






Nodes



19k





Edges



44k





Density



0.00023





Maximum degree



171





Minimum degree



1





Average degree



4.50





Assortativity



0.145





Number of triangles



13144





Average number of triangles



0.67





Maximum number of triangles



322





Average clustering coefficient



0.633





Fraction of closed triangles



0.051





Maximum k-core



24





Lower bound of Maximum Clique



8





 

 

 

Network Data Statistics DBLP






Nodes



12.6K





Edges



49.7K





Density



0.000627401





Maximum degree



710





Minimum degree



1





Average degree



7





Assortativity



-0.0455856





Number of triangles



133.9K





Average number of triangles



10





Maximum number of triangles



2.5K





Average clustering coefficient



0.119232





Fraction of closed triangles



0.0628303





Maximum k-core



13





Lower bound of Maximum Clique



8