Discovering eras in evolving social networks (extended abstract)

Michele Berlingerio, Michele Coscia, Fosca Giannotti, Anna Monreale, Dino Pedreschi

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Abstract

An important topic in complex network research is the temporal evolution of networks. Existing approaches aim at analyzing the evolution extracting properties of either the entire network or local patterns. In this paper, we focus on detecting clusters of temporal snapshots of a network, to be interpreted as eras of evolution. To this aim, we introduce a novel hierarchical clustering methodology, based on a dissimilarity measure between two temporal snapshots of the network. We devise a framework to discover and browse the eras, supporting the exploration of the evolution at any level of temporal resolution. We show how our approach applies to real networks, by detecting eras in an evolving co-authorship graph; we illustrate how the discovered temporal clustering highlights the crucial moments when the network had profound changes in its structure. Our approach is finally boosted by introducing a meaningful labeling of the obtained clusters, such as the characterizing topics of each discovered era, thus adding a semantic dimension to our analysis.

Original languageEnglish
Title of host publicationSEBD 2010 - Proceedings of the 18th Italian Symposium on Advanced Database Systems
PublisherEsculapio Editore
Pages78-85
Number of pages8
ISBN (Print)9788874883691
Publication statusPublished - 2010
Externally publishedYes
Event18th Italian Symposium on Advanced Database Systems, SEBD 2010 - Rimini, Italy
Duration: 20 Jun 201023 Jun 2010

Conference

Conference18th Italian Symposium on Advanced Database Systems, SEBD 2010
CountryItaly
CityRimini
Period20/06/1023/06/10

Fingerprint

Complex networks
Labeling
Semantics

Cite this

Berlingerio, M., Coscia, M., Giannotti, F., Monreale, A., & Pedreschi, D. (2010). Discovering eras in evolving social networks (extended abstract). In SEBD 2010 - Proceedings of the 18th Italian Symposium on Advanced Database Systems (pp. 78-85). Esculapio Editore.
Berlingerio, Michele ; Coscia, Michele ; Giannotti, Fosca ; Monreale, Anna ; Pedreschi, Dino. / Discovering eras in evolving social networks (extended abstract). SEBD 2010 - Proceedings of the 18th Italian Symposium on Advanced Database Systems. Esculapio Editore, 2010. pp. 78-85
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title = "Discovering eras in evolving social networks (extended abstract)",
abstract = "An important topic in complex network research is the temporal evolution of networks. Existing approaches aim at analyzing the evolution extracting properties of either the entire network or local patterns. In this paper, we focus on detecting clusters of temporal snapshots of a network, to be interpreted as eras of evolution. To this aim, we introduce a novel hierarchical clustering methodology, based on a dissimilarity measure between two temporal snapshots of the network. We devise a framework to discover and browse the eras, supporting the exploration of the evolution at any level of temporal resolution. We show how our approach applies to real networks, by detecting eras in an evolving co-authorship graph; we illustrate how the discovered temporal clustering highlights the crucial moments when the network had profound changes in its structure. Our approach is finally boosted by introducing a meaningful labeling of the obtained clusters, such as the characterizing topics of each discovered era, thus adding a semantic dimension to our analysis.",
author = "Michele Berlingerio and Michele Coscia and Fosca Giannotti and Anna Monreale and Dino Pedreschi",
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Berlingerio, M, Coscia, M, Giannotti, F, Monreale, A & Pedreschi, D 2010, Discovering eras in evolving social networks (extended abstract). in SEBD 2010 - Proceedings of the 18th Italian Symposium on Advanced Database Systems. Esculapio Editore, pp. 78-85, 18th Italian Symposium on Advanced Database Systems, SEBD 2010, Rimini, Italy, 20/06/10.

Discovering eras in evolving social networks (extended abstract). / Berlingerio, Michele; Coscia, Michele; Giannotti, Fosca; Monreale, Anna; Pedreschi, Dino.

SEBD 2010 - Proceedings of the 18th Italian Symposium on Advanced Database Systems. Esculapio Editore, 2010. p. 78-85.

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

TY - GEN

T1 - Discovering eras in evolving social networks (extended abstract)

AU - Berlingerio, Michele

AU - Coscia, Michele

AU - Giannotti, Fosca

AU - Monreale, Anna

AU - Pedreschi, Dino

PY - 2010

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N2 - An important topic in complex network research is the temporal evolution of networks. Existing approaches aim at analyzing the evolution extracting properties of either the entire network or local patterns. In this paper, we focus on detecting clusters of temporal snapshots of a network, to be interpreted as eras of evolution. To this aim, we introduce a novel hierarchical clustering methodology, based on a dissimilarity measure between two temporal snapshots of the network. We devise a framework to discover and browse the eras, supporting the exploration of the evolution at any level of temporal resolution. We show how our approach applies to real networks, by detecting eras in an evolving co-authorship graph; we illustrate how the discovered temporal clustering highlights the crucial moments when the network had profound changes in its structure. Our approach is finally boosted by introducing a meaningful labeling of the obtained clusters, such as the characterizing topics of each discovered era, thus adding a semantic dimension to our analysis.

AB - An important topic in complex network research is the temporal evolution of networks. Existing approaches aim at analyzing the evolution extracting properties of either the entire network or local patterns. In this paper, we focus on detecting clusters of temporal snapshots of a network, to be interpreted as eras of evolution. To this aim, we introduce a novel hierarchical clustering methodology, based on a dissimilarity measure between two temporal snapshots of the network. We devise a framework to discover and browse the eras, supporting the exploration of the evolution at any level of temporal resolution. We show how our approach applies to real networks, by detecting eras in an evolving co-authorship graph; we illustrate how the discovered temporal clustering highlights the crucial moments when the network had profound changes in its structure. Our approach is finally boosted by introducing a meaningful labeling of the obtained clusters, such as the characterizing topics of each discovered era, thus adding a semantic dimension to our analysis.

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M3 - Conference contribution

SN - 9788874883691

SP - 78

EP - 85

BT - SEBD 2010 - Proceedings of the 18th Italian Symposium on Advanced Database Systems

PB - Esculapio Editore

ER -

Berlingerio M, Coscia M, Giannotti F, Monreale A, Pedreschi D. Discovering eras in evolving social networks (extended abstract). In SEBD 2010 - Proceedings of the 18th Italian Symposium on Advanced Database Systems. Esculapio Editore. 2010. p. 78-85