Results 31 to 40 of about 1,651,191 (277)

A maximal clique based multiobjective evolutionary algorithm for overlapping community detection [PDF]

, 2016
Detecting community structure has become one im-portant technique for studying complex networks. Although many community detection algorithms have been proposed, most of them focus on separated communities, where each node can be-long to only one ...
Chen, Wei-Neng, Gu, Tianlong, Li, Yun, Lin, Ying, Wen, Xuyun, Yin, Yilong, Zhang, Huaxiang, Zhang, Jun   +7 more
core   +2 more sources

Spectral Clustering Community Detection Algorithm Based on Point-Wise Mutual Information Graph Kernel

Entropy, 2023
To address the problem that traditional spectral clustering algorithms cannot obtain the complete structural information of networks, this paper proposes a spectral clustering community detection algorithm, PMIK-SC, based on the point-wise mutual ...
Yinan Chen, Wenbin Ye, Dong Li
doaj   +1 more source

Intrinsically Dynamic Network Communities [PDF]

, 2011
Community finding algorithms for networks have recently been extended to dynamic data. Most of these recent methods aim at exhibiting community partitions from successive graph snapshots and thereafter connecting or smoothing these partitions using ...
Mitra, Bivas, Roth, Camille, Tabourier, Lionel   +2 more
core   +5 more sources

Post-Processing Partitions to Identify Domains of Modularity Optimization

Algorithms, 2017
We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of possibly various computational heuristics.
William H. Weir, Scott Emmons, Ryan Gibson, Dane Taylor, Peter J. Mucha   +4 more
doaj   +1 more source

Sociolect-based community detection [PDF]

2013 IEEE International Conference on Intelligence and Security Informatics, 2013
'Sociolects' are specialized vocabularies used by social subgroups defined by common interests or origins. We applied methods to retrieve large quantities of Twitter data based on expert-identified sociolects and then applied and developed network-analysis methods to relate sociolect use to network (sub-) structure. We show that novel methods including
Reynolds, William N., Salter, William J., Farber, Robert M., Corley, Courtney, Dowling, Chase P., Beeman, William O., Smith-Lovin, Lynn, Choi, Joon Nak   +7 more
openaire   +1 more source

Analyzing the Spread of Misinformation on Social Networks: A Process and Software Architecture for Detection and Analysis

Computers, 2023
The rapid dissemination of misinformation on social networks, particularly during public health crises like the COVID-19 pandemic, has become a significant concern.
Zafer Duzen, Mirela Riveni, Mehmet S. Aktas   +2 more
doaj   +1 more source

Co-Community Network Analysis Reveals Alterations in Brain Networks in Alzheimer’s Disease

Brain Sciences
Background: Alzheimer’s disease (AD) is a common neurodegenerative disease. Functional magnetic resonance imaging (fMRI) can be used to measure the temporal correlation of blood-oxygen-level-dependent (BOLD) signals in the brain to assess the brain’s ...
Xiaodong Wang, Zhaokai Zhang, Lingli Deng, Jiyang Dong   +3 more
doaj   +1 more source

Learner2Vec-Based Learner Community Evolution Analysis–A Case Study Involving Student Card Data

IEEE Access, 2019
The learner community evolution analysis is an important technique in the area of social network analysis and education management. Accurately expressing the complex characteristics of individual social behavior is the core problem associated with ...
Chao Li, Lei Zhao, Qingtian Zeng, Hua Duan, Zhongying Zhao   +4 more
doaj   +1 more source

CoDiS: Community Detection via Distributed Seed Set Expansion on Graph Streams

Information, 2023
Community detection has been (and remains) a very important topic in several fields. From marketing and social networking to biological studies, community detection plays a key role in advancing research in many different fields.
Austin Anderson, Petros Potikas, Katerina Potika   +2 more
doaj   +1 more source

Terminal-Set-Enhanced Community Detection in Social Networks

, 2016
Community detection aims to reveal the community structure in a social network, which is one of the fundamental problems. In this paper we investigate the community detection problem based on the concept of terminal set.
Cui, L., Du, D-Z., Liu, C., Tong, G., Wu, W.   +4 more
core   +1 more source