#### DMCA

## A Dynamic Modularity Based Community Detection Algorithm for Large-scale Networks: DSLM

### Citations

971 |
Modularity and community structure in networks
- Newman
(Show Context)
Citation Context ...rves the degree of each vertex of the original graph. With this null model, modularity is calculated as the fraction of edges that fall in the given communities minus such fraction in the null model. =-=[23]-=-, [24] The formula of modularity can be written as in Equation 1 Q = 1 2m ∑ ij (Aij − Pij)δ(Ci, Cj) (1) m represents the total number of edges of the graph. Sum iterates over all vertices denoted as i... |

813 | Community detection in graphs
- Fortunato
- 2010
(Show Context)
Citation Context ...he degree of each vertex of the original graph. With this null model, modularity is calculated as the fraction of edges that fall in the given communities minus such fraction in the null model. [23], =-=[24]-=- The formula of modularity can be written as in Equation 1 Q = 1 2m ∑ ij (Aij − Pij)δ(Ci, Cj) (1) m represents the total number of edges of the graph. Sum iterates over all vertices denoted as i and j... |

694 | B.: Measurement and analysis of online social networks
- Mislove, Marcon, et al.
- 2007
(Show Context)
Citation Context ...oject2. The Google Plus data consists of 107,614 nodes and 13,673,453 edges. The Twitter data consists of 81,306 nodes and 1,768,149 edges. The Youtube user network data is provided by Mislove et al. =-=[32]-=-. It consists of 1,134,890 nodes and 2,987,624 edges. The users of the Youtube are the nodes, and the friendships are represented by edges. We used these 3 datasets for node deletion and addition expe... |

687 |
Finding community structure in very large networks
- Clauset, Newman, et al.
(Show Context)
Citation Context ... the users and the edges represent the calls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as =-=[1]-=-, [2], [3], [4], [5], [6], [7], [8], [9] proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks a... |

586 | Fast unfolding of communities in large networks
- Blondel, Guillaume, et al.
(Show Context)
Citation Context ...sent the calls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as [1], [2], [3], [4], [5], [6], =-=[7]-=-, [8], [9] proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks are not static because they evo... |

494 | Finding Community Structure in Networks Using the Eigenvectors of Matrices
- Newman
(Show Context)
Citation Context ...the edges represent the calls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as [1], [2], [3], =-=[4]-=-, [5], [6], [7], [8], [9] proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks are not static b... |

309 |
Resolution limit in community detection
- Fortunato, Barthélemy
- 2007
(Show Context)
Citation Context ...ffer a resolution parameter that makes it possible to customize the granularity level at which communities are detected and to mitigate the resolution limit problem defined by Fortunato and Barthlemy =-=[28]-=-. [29] Moreover, there are modularity functions with a somewhat modified mathematical structure in the literature such as Reichardt & Bornholdt, 2006; Traag, Van Dooren, & Nesterov, 2011; Waltman, Van... |

152 |
A.: Community detection in complex networks using extremal optimization
- Duch, Arenas
- 2005
(Show Context)
Citation Context ... and the edges represent the calls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as [1], [2], =-=[3]-=-, [4], [5], [6], [7], [8], [9] proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks are not sta... |

148 | On modularity clustering - Brandes, Delling, et al. |

131 |
Evolutionary clustering
- Chakrabarti, Kumar, et al.
- 2006
(Show Context)
Citation Context ...6] A methodology that tries to find an optimal cluster sequence by detecting a cluster structure at each timestamp that optimizes the incremental quality can be classified as evolutionary clustering. =-=[17]-=-, [18] Furthermore, tracking algorithms based on similarity comparison have also been studied in order to be able to describe the change of communities on the time axis. [19], [20] Apart from these al... |

99 |
Modularity from fluctuations in random graphs and complex networks, Phys
- Guimerà, Sales-Pardo, et al.
- 2004
(Show Context)
Citation Context ...users and the edges represent the calls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as [1], =-=[2]-=-, [3], [4], [5], [6], [7], [8], [9] proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks are no... |

84 |
Temporal networks.
- Holme, Saramäki
- 2012
(Show Context)
Citation Context ...as Smart Local Moving (SLM) algorithm that is proposed by Waltman and Jan van Eck in 2013. [9] SLM algorithm is explained in detail in chapter III. Due to the dynamic features of many social networks =-=[14]-=-, the need for detecting communities dynamically in the large networks is emerged in the latest years. There have been many community detection algorithms proposed in the literature to fulfill this ne... |

48 | Analyzing Communities and Their Evolutions in Dynamic Social Networks.
- Lin, Chi, et al.
- 2009
(Show Context)
Citation Context ...ill this need. Xu et al. divides the current research on community evolution into the following categories. Parameter estimation methods and probabilistic models have been proposed in the literature. =-=[15]-=-, [16] A methodology that tries to find an optimal cluster sequence by detecting a cluster structure at each timestamp that optimizes the incremental quality can be classified as evolutionary clusteri... |

40 | Tracking the evolution of communities in dynamic social networks.
- Greene, Doyle, et al.
- 2010
(Show Context)
Citation Context ... evolutionary clustering. [17], [18] Furthermore, tracking algorithms based on similarity comparison have also been studied in order to be able to describe the change of communities on the time axis. =-=[19]-=-, [20] Apart from these algorithms that are focused on the evolution procedures of communities, community detection in dynamic social networks aims to detect the optimal community structure at each ti... |

35 | A particle-and-density based evolutionary clustering method for dynamic networks
- Kim, Han
- 2009
(Show Context)
Citation Context ...ethodology that tries to find an optimal cluster sequence by detecting a cluster structure at each timestamp that optimizes the incremental quality can be classified as evolutionary clustering. [17], =-=[18]-=- Furthermore, tracking algorithms based on similarity comparison have also been studied in order to be able to describe the change of communities on the time axis. [19], [20] Apart from these algorith... |

32 | Size reduction of complex networks preserving modularity
- Arenas, Duch, et al.
- 2007
(Show Context)
Citation Context ... means the degree of vertex i and vertex j respectively. [24] Apart from weighted networks, the modularity function defined in 3 has been extended in order to be also applicable to directed networks. =-=[26]-=-, [27] When the edges are directed, stubs will also be directed and it changes the possibility of rewiring stubs and connecting edges. The calculation of this possibility in the directed case depends ... |

22 |
Community structure in directed networks,” Phys
- Leicht, Newman
- 2008
(Show Context)
Citation Context ... the degree of vertex i and vertex j respectively. [24] Apart from weighted networks, the modularity function defined in 3 has been extended in order to be also applicable to directed networks. [26], =-=[27]-=- When the edges are directed, stubs will also be directed and it changes the possibility of rewiring stubs and connecting edges. The calculation of this possibility in the directed case depends on the... |

18 | Analysis of weighted networks,” Phys - Newman - 2004 |

18 |
Narrow scope for resolution-limit-free community detection,” Phys
- Traag, Dooren, et al.
- 2011
(Show Context)
Citation Context ...rity functions with a somewhat modified mathematical structure in the literature such as Reichardt & Bornholdt, 2006; Traag, Van Dooren, & Nesterov, 2011; Waltman, Van Eck, & Noyons, 2010. [9], [28], =-=[30]-=-, [31] IV. SLM AND DSLM ALGORITHMS A. SLM Algorithm SLM is a community detection algorithm that is evolved from Louvain algorithm. Louvain algorithm is a large scale modularity based community detecti... |

16 |
Column generation algorithms for exact modularity maximization in networks
- Aloise, Cafieri, et al.
(Show Context)
Citation Context ...tex of the given network to a community such that it maximizes the modularity value of the network. Optimizing modularity is an NP-hard problem. [10] Exact algorithms that maximize modularity such as =-=[11]-=-, [10], [12] can be used only for small networks. For large-scale modularity optimization, heuristic algorithms are proposed. We basically focus on three well known algorithms, namely; CNM, Louvain an... |

15 |
A unified approach to mapping and clustering of bibliometric networks.
- Waltman, Eck, et al.
- 2010
(Show Context)
Citation Context ...unctions with a somewhat modified mathematical structure in the literature such as Reichardt & Bornholdt, 2006; Traag, Van Dooren, & Nesterov, 2011; Waltman, Van Eck, & Noyons, 2010. [9], [28], [30], =-=[31]-=- IV. SLM AND DSLM ALGORITHMS A. SLM Algorithm SLM is a community detection algorithm that is evolved from Louvain algorithm. Louvain algorithm is a large scale modularity based community detection alg... |

13 |
Multilevel local search algorithms for modularity clustering
- Rotta, Noack
- 2011
(Show Context)
Citation Context ...the calls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as [1], [2], [3], [4], [5], [6], [7], =-=[8]-=-, [9] proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks are not static because they evolve i... |

12 | Static community detection algorithms for evolving networks
- Aynaud, Guillaume
- 2010
(Show Context)
Citation Context ...l networks aims to detect the optimal community structure at each timestamp. For this purpose, incremental versions of both CNM and Louvain algorithm are proposed by Dinh et al.[21] and Aynaud et al. =-=[22]-=-. To the best of our knowledge, this is the first work considering the incremental version of Smart Local Moving algorithm in literature. Our algorithm can be classified as the last mentioned category... |

11 | Towards social-aware routing in dynamic communication networks
- Dinh, Xuan, et al.
- 2009
(Show Context)
Citation Context ...ection in dynamic social networks aims to detect the optimal community structure at each timestamp. For this purpose, incremental versions of both CNM and Louvain algorithm are proposed by Dinh et al.=-=[21]-=- and Aynaud et al. [22]. To the best of our knowledge, this is the first work considering the incremental version of Smart Local Moving algorithm in literature. Our algorithm can be classified as the ... |

9 |
Finding community structures in complex networks using mixed integer optimisation
- Xu, Tsoka, et al.
(Show Context)
Citation Context ...iven network to a community such that it maximizes the modularity value of the network. Optimizing modularity is an NP-hard problem. [10] Exact algorithms that maximize modularity such as [11], [10], =-=[12]-=- can be used only for small networks. For large-scale modularity optimization, heuristic algorithms are proposed. We basically focus on three well known algorithms, namely; CNM, Louvain and SLM. The f... |

4 |
Group evolution discovery in social networks
- Bródka, Saganowski, et al.
- 2011
(Show Context)
Citation Context ...tionary clustering. [17], [18] Furthermore, tracking algorithms based on similarity comparison have also been studied in order to be able to describe the change of communities on the time axis. [19], =-=[20]-=- Apart from these algorithms that are focused on the evolution procedures of communities, community detection in dynamic social networks aims to detect the optimal community structure at each timestam... |

3 |
Deterministic modularity optimization,” The European
- Lehmann, Hansen
- 2007
(Show Context)
Citation Context ...dges represent the calls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as [1], [2], [3], [4], =-=[5]-=-, [6], [7], [8], [9] proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks are not static becaus... |

3 |
Mod-CSA: Modularity optimization by conformational space annealing
- Lee, SP, et al.
- 2012
(Show Context)
Citation Context ...represent the calls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as [1], [2], [3], [4], [5], =-=[6]-=-, [7], [8], [9] proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks are not static because the... |

3 |
A smart local moving algorithm for large-scale modularity-based community detection
- Waltman, Eck
- 2013
(Show Context)
Citation Context ...alls that users made. The detection of communities in these large networks is a problem in this area; therefore a lot of community detection algorithms such as [1], [2], [3], [4], [5], [6], [7], [8], =-=[9]-=- proposed in the literature. Almost all these community detection algorithms are static and designed for static networks. However, most of the social networks are not static because they evolve in man... |

3 |
Statistical mechanics of community detection. arXiv
- Reichardt, Bornholdt
- 2006
(Show Context)
Citation Context ... resolution parameter that makes it possible to customize the granularity level at which communities are detected and to mitigate the resolution limit problem defined by Fortunato and Barthlemy [28]. =-=[29]-=- Moreover, there are modularity functions with a somewhat modified mathematical structure in the literature such as Reichardt & Bornholdt, 2006; Traag, Van Dooren, & Nesterov, 2011; Waltman, Van Eck, ... |

2 | Dynamic community detection with temporal dirichlet process
- Tang, Yang
(Show Context)
Citation Context ...is need. Xu et al. divides the current research on community evolution into the following categories. Parameter estimation methods and probabilistic models have been proposed in the literature. [15], =-=[16]-=- A methodology that tries to find an optimal cluster sequence by detecting a cluster structure at each timestamp that optimizes the incremental quality can be classified as evolutionary clustering. [1... |