SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks

Konstantinos Skianis; Maria Evgenia G. Rossi; Fragkiskos D. Malliaros; Michalis Vazirgiannis

doi:10.1109/ICDMW.2016.0195

SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks

Konstantinos Skianis
, Maria Evgenia G. Rossi
, Fragkiskos D. Malliaros
, Michalis Vazirgiannis

Computer Science Laboratory
Laboratoire d'Informatique (LIX)
University of California, San Diego

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

In this paper, we propose SpreadViz, a web tool for exploration and visualization of spreading processes in social networks. SpreadViz consists of three main modules, namely graph exploration and analytics, detection of influential nodes, and interactive visualization. More precisely, SpreadViz offers the following functionalities: (i) It computes and visualizes various centrality criteria towards understanding how the position of a node in the network affects its spreading properties, (ii) It offers a wide range of criteria for the detection of single and multiple influential nodes and comparison among them, (iii) It effectively visualizes the spread of influence in the network as well as the performance of each method. In our demonstration, we invite the audience to interact with SpreadViz, exploring, analyzing, and visualizing the spreading processes over various real-world social networks. The tool is available online.

Original language	English
Title of host publication	Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
Editors	Carlotta Domeniconi, Francesco Gullo, Francesco Bonchi, Francesco Bonchi, Josep Domingo-Ferrer, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Zhi-Hua Zhou, Xindong Wu
Publisher	IEEE Computer Society
Pages	1324-1327
Number of pages	4
ISBN (Electronic)	9781509054725
DOIs	https://doi.org/10.1109/ICDMW.2016.0195
Publication status	Published - 2 Jul 2016
Event	16th IEEE International Conference on Data Mining Workshops, ICDMW 2016 - Barcelona, Spain Duration: 12 Dec 2016 → 15 Dec 2016

Publication series

Name	IEEE International Conference on Data Mining Workshops, ICDMW
Volume	0
ISSN (Print)	2375-9232
ISSN (Electronic)	2375-9259

Conference

Conference	16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
Country/Territory	Spain
City	Barcelona
Period	12/12/16 → 15/12/16

Keywords

Graph Mining
Influence Maximization
Influential Spreaders
Social Network Analysis

Access to Document

10.1109/ICDMW.2016.0195

Cite this

Skianis, K., Rossi, M. E. G., Malliaros, F. D., & Vazirgiannis, M. (2016). SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks. In C. Domeniconi, F. Gullo, F. Bonchi, F. Bonchi, J. Domingo-Ferrer, R. Baeza-Yates, R. Baeza-Yates, R. Baeza-Yates, Z.-H. Zhou, & X. Wu (Eds.), Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016 (pp. 1324-1327). Article 7836826 (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 0). IEEE Computer Society. https://doi.org/10.1109/ICDMW.2016.0195

Skianis, Konstantinos ; Rossi, Maria Evgenia G. ; Malliaros, Fragkiskos D. et al. / SpreadViz : Analytics and Visualization of Spreading Processes in Social Networks. Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016. editor / Carlotta Domeniconi ; Francesco Gullo ; Francesco Bonchi ; Francesco Bonchi ; Josep Domingo-Ferrer ; Ricardo Baeza-Yates ; Ricardo Baeza-Yates ; Ricardo Baeza-Yates ; Zhi-Hua Zhou ; Xindong Wu. IEEE Computer Society, 2016. pp. 1324-1327 (IEEE International Conference on Data Mining Workshops, ICDMW).

@inproceedings{54e6db31438f4c6582ee2dd205f8b7b2,

title = "SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks",

abstract = "In this paper, we propose SpreadViz, a web tool for exploration and visualization of spreading processes in social networks. SpreadViz consists of three main modules, namely graph exploration and analytics, detection of influential nodes, and interactive visualization. More precisely, SpreadViz offers the following functionalities: (i) It computes and visualizes various centrality criteria towards understanding how the position of a node in the network affects its spreading properties, (ii) It offers a wide range of criteria for the detection of single and multiple influential nodes and comparison among them, (iii) It effectively visualizes the spread of influence in the network as well as the performance of each method. In our demonstration, we invite the audience to interact with SpreadViz, exploring, analyzing, and visualizing the spreading processes over various real-world social networks. The tool is available online.",

keywords = "Graph Mining, Influence Maximization, Influential Spreaders, Social Network Analysis",

author = "Konstantinos Skianis and Rossi, \{Maria Evgenia G.\} and Malliaros, \{Fragkiskos D.\} and Michalis Vazirgiannis",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016 ; Conference date: 12-12-2016 Through 15-12-2016",

year = "2016",

month = jul,

day = "2",

doi = "10.1109/ICDMW.2016.0195",

language = "English",

series = "IEEE International Conference on Data Mining Workshops, ICDMW",

publisher = "IEEE Computer Society",

pages = "1324--1327",

editor = "Carlotta Domeniconi and Francesco Gullo and Francesco Bonchi and Francesco Bonchi and Josep Domingo-Ferrer and Ricardo Baeza-Yates and Ricardo Baeza-Yates and Ricardo Baeza-Yates and Zhi-Hua Zhou and Xindong Wu",

booktitle = "Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016",

}

Skianis, K, Rossi, MEG, Malliaros, FD & Vazirgiannis, M 2016, SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks. in C Domeniconi, F Gullo, F Bonchi, F Bonchi, J Domingo-Ferrer, R Baeza-Yates, R Baeza-Yates, R Baeza-Yates, Z-H Zhou & X Wu (eds), Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016., 7836826, IEEE International Conference on Data Mining Workshops, ICDMW, vol. 0, IEEE Computer Society, pp. 1324-1327, 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016, Barcelona, Spain, 12/12/16. https://doi.org/10.1109/ICDMW.2016.0195

SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks. / Skianis, Konstantinos; Rossi, Maria Evgenia G.; Malliaros, Fragkiskos D. et al.
Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016. ed. / Carlotta Domeniconi; Francesco Gullo; Francesco Bonchi; Francesco Bonchi; Josep Domingo-Ferrer; Ricardo Baeza-Yates; Ricardo Baeza-Yates; Ricardo Baeza-Yates; Zhi-Hua Zhou; Xindong Wu. IEEE Computer Society, 2016. p. 1324-1327 7836826 (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 0).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - SpreadViz

T2 - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016

AU - Skianis, Konstantinos

AU - Rossi, Maria Evgenia G.

AU - Malliaros, Fragkiskos D.

AU - Vazirgiannis, Michalis

PY - 2016/7/2

Y1 - 2016/7/2

N2 - In this paper, we propose SpreadViz, a web tool for exploration and visualization of spreading processes in social networks. SpreadViz consists of three main modules, namely graph exploration and analytics, detection of influential nodes, and interactive visualization. More precisely, SpreadViz offers the following functionalities: (i) It computes and visualizes various centrality criteria towards understanding how the position of a node in the network affects its spreading properties, (ii) It offers a wide range of criteria for the detection of single and multiple influential nodes and comparison among them, (iii) It effectively visualizes the spread of influence in the network as well as the performance of each method. In our demonstration, we invite the audience to interact with SpreadViz, exploring, analyzing, and visualizing the spreading processes over various real-world social networks. The tool is available online.

AB - In this paper, we propose SpreadViz, a web tool for exploration and visualization of spreading processes in social networks. SpreadViz consists of three main modules, namely graph exploration and analytics, detection of influential nodes, and interactive visualization. More precisely, SpreadViz offers the following functionalities: (i) It computes and visualizes various centrality criteria towards understanding how the position of a node in the network affects its spreading properties, (ii) It offers a wide range of criteria for the detection of single and multiple influential nodes and comparison among them, (iii) It effectively visualizes the spread of influence in the network as well as the performance of each method. In our demonstration, we invite the audience to interact with SpreadViz, exploring, analyzing, and visualizing the spreading processes over various real-world social networks. The tool is available online.

KW - Graph Mining

KW - Influence Maximization

KW - Influential Spreaders

KW - Social Network Analysis

U2 - 10.1109/ICDMW.2016.0195

DO - 10.1109/ICDMW.2016.0195

M3 - Conference contribution

AN - SCOPUS:85015160923

T3 - IEEE International Conference on Data Mining Workshops, ICDMW

SP - 1324

EP - 1327

BT - Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016

A2 - Domeniconi, Carlotta

A2 - Gullo, Francesco

A2 - Bonchi, Francesco

A2 - Domingo-Ferrer, Josep

A2 - Baeza-Yates, Ricardo

A2 - Zhou, Zhi-Hua

A2 - Wu, Xindong

PB - IEEE Computer Society

Y2 - 12 December 2016 through 15 December 2016

ER -

Skianis K, Rossi MEG, Malliaros FD, Vazirgiannis M. SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks. In Domeniconi C, Gullo F, Bonchi F, Bonchi F, Domingo-Ferrer J, Baeza-Yates R, Baeza-Yates R, Baeza-Yates R, Zhou ZH, Wu X, editors, Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016. IEEE Computer Society. 2016. p. 1324-1327. 7836826. (IEEE International Conference on Data Mining Workshops, ICDMW). doi: 10.1109/ICDMW.2016.0195

SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks

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Keywords

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