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
N1 - Publisher Copyright:
© 2016 IEEE.
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 - Bonchi, Francesco
A2 - Domingo-Ferrer, Josep
A2 - Baeza-Yates, Ricardo
A2 - Baeza-Yates, Ricardo
A2 - Baeza-Yates, Ricardo
A2 - Zhou, Zhi-Hua
A2 - Wu, Xindong
PB - IEEE Computer Society
Y2 - 12 December 2016 through 15 December 2016
ER -