Communities and hierarchical structures in dynamic social networks: analysis and visualization
Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchi...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gilbert, Frédéric [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2010 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© Springer-Verlag 2010 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Social network analysis and mining - Wien : Springer, 2011, 1(2010), 2 vom: 05. Okt., Seite 83-95 |
|---|---|
| Übergeordnetes Werk: |
volume:1 ; year:2010 ; number:2 ; day:05 ; month:10 ; pages:83-95 |
| Links: |
|---|
| DOI / URN: |
10.1007/s13278-010-0002-8 |
|---|
| Katalog-ID: |
SPR031180566 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | SPR031180566 | ||
| 003 | DE-627 | ||
| 005 | 20230331070416.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 201007s2010 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s13278-010-0002-8 |2 doi | |
| 035 | |a (DE-627)SPR031180566 | ||
| 035 | |a (SPR)s13278-010-0002-8-e | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Gilbert, Frédéric |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Communities and hierarchical structures in dynamic social networks: analysis and visualization |
| 264 | 1 | |c 2010 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a © Springer-Verlag 2010 | ||
| 520 | |a Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. | ||
| 650 | 4 | |a Dynamic social networks |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Dynamic network visualization |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Clustering dynamic graphs |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Influence hierarchy in social networks |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Simonetto, Paolo |4 aut | |
| 700 | 1 | |a Zaidi, Faraz |4 aut | |
| 700 | 1 | |a Jourdan, Fabien |4 aut | |
| 700 | 1 | |a Bourqui, Romain |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Social network analysis and mining |d Wien : Springer, 2011 |g 1(2010), 2 vom: 05. Okt., Seite 83-95 |w (DE-627)647305739 |w (DE-600)2595306-0 |x 1869-5469 |7 nnns |
| 773 | 1 | 8 | |g volume:1 |g year:2010 |g number:2 |g day:05 |g month:10 |g pages:83-95 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.1007/s13278-010-0002-8 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_SPRINGER | ||
| 951 | |a AR | ||
| 952 | |d 1 |j 2010 |e 2 |b 05 |c 10 |h 83-95 | ||
| author_variant |
f g fg p s ps f z fz f j fj r b rb |
|---|---|
| matchkey_str |
article:18695469:2010----::omnteadirrhcltutrsnyaiscantoka |
| hierarchy_sort_str |
2010 |
| publishDate |
2010 |
| allfields |
10.1007/s13278-010-0002-8 doi (DE-627)SPR031180566 (SPR)s13278-010-0002-8-e DE-627 ger DE-627 rakwb eng Gilbert, Frédéric verfasserin aut Communities and hierarchical structures in dynamic social networks: analysis and visualization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2010 Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. Dynamic social networks (dpeaa)DE-He213 Dynamic network visualization (dpeaa)DE-He213 Clustering dynamic graphs (dpeaa)DE-He213 Influence hierarchy in social networks (dpeaa)DE-He213 Simonetto, Paolo aut Zaidi, Faraz aut Jourdan, Fabien aut Bourqui, Romain aut Enthalten in Social network analysis and mining Wien : Springer, 2011 1(2010), 2 vom: 05. Okt., Seite 83-95 (DE-627)647305739 (DE-600)2595306-0 1869-5469 nnns volume:1 year:2010 number:2 day:05 month:10 pages:83-95 https://dx.doi.org/10.1007/s13278-010-0002-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 1 2010 2 05 10 83-95 |
| spelling |
10.1007/s13278-010-0002-8 doi (DE-627)SPR031180566 (SPR)s13278-010-0002-8-e DE-627 ger DE-627 rakwb eng Gilbert, Frédéric verfasserin aut Communities and hierarchical structures in dynamic social networks: analysis and visualization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2010 Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. Dynamic social networks (dpeaa)DE-He213 Dynamic network visualization (dpeaa)DE-He213 Clustering dynamic graphs (dpeaa)DE-He213 Influence hierarchy in social networks (dpeaa)DE-He213 Simonetto, Paolo aut Zaidi, Faraz aut Jourdan, Fabien aut Bourqui, Romain aut Enthalten in Social network analysis and mining Wien : Springer, 2011 1(2010), 2 vom: 05. Okt., Seite 83-95 (DE-627)647305739 (DE-600)2595306-0 1869-5469 nnns volume:1 year:2010 number:2 day:05 month:10 pages:83-95 https://dx.doi.org/10.1007/s13278-010-0002-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 1 2010 2 05 10 83-95 |
| allfields_unstemmed |
10.1007/s13278-010-0002-8 doi (DE-627)SPR031180566 (SPR)s13278-010-0002-8-e DE-627 ger DE-627 rakwb eng Gilbert, Frédéric verfasserin aut Communities and hierarchical structures in dynamic social networks: analysis and visualization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2010 Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. Dynamic social networks (dpeaa)DE-He213 Dynamic network visualization (dpeaa)DE-He213 Clustering dynamic graphs (dpeaa)DE-He213 Influence hierarchy in social networks (dpeaa)DE-He213 Simonetto, Paolo aut Zaidi, Faraz aut Jourdan, Fabien aut Bourqui, Romain aut Enthalten in Social network analysis and mining Wien : Springer, 2011 1(2010), 2 vom: 05. Okt., Seite 83-95 (DE-627)647305739 (DE-600)2595306-0 1869-5469 nnns volume:1 year:2010 number:2 day:05 month:10 pages:83-95 https://dx.doi.org/10.1007/s13278-010-0002-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 1 2010 2 05 10 83-95 |
| allfieldsGer |
10.1007/s13278-010-0002-8 doi (DE-627)SPR031180566 (SPR)s13278-010-0002-8-e DE-627 ger DE-627 rakwb eng Gilbert, Frédéric verfasserin aut Communities and hierarchical structures in dynamic social networks: analysis and visualization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2010 Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. Dynamic social networks (dpeaa)DE-He213 Dynamic network visualization (dpeaa)DE-He213 Clustering dynamic graphs (dpeaa)DE-He213 Influence hierarchy in social networks (dpeaa)DE-He213 Simonetto, Paolo aut Zaidi, Faraz aut Jourdan, Fabien aut Bourqui, Romain aut Enthalten in Social network analysis and mining Wien : Springer, 2011 1(2010), 2 vom: 05. Okt., Seite 83-95 (DE-627)647305739 (DE-600)2595306-0 1869-5469 nnns volume:1 year:2010 number:2 day:05 month:10 pages:83-95 https://dx.doi.org/10.1007/s13278-010-0002-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 1 2010 2 05 10 83-95 |
| allfieldsSound |
10.1007/s13278-010-0002-8 doi (DE-627)SPR031180566 (SPR)s13278-010-0002-8-e DE-627 ger DE-627 rakwb eng Gilbert, Frédéric verfasserin aut Communities and hierarchical structures in dynamic social networks: analysis and visualization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2010 Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. Dynamic social networks (dpeaa)DE-He213 Dynamic network visualization (dpeaa)DE-He213 Clustering dynamic graphs (dpeaa)DE-He213 Influence hierarchy in social networks (dpeaa)DE-He213 Simonetto, Paolo aut Zaidi, Faraz aut Jourdan, Fabien aut Bourqui, Romain aut Enthalten in Social network analysis and mining Wien : Springer, 2011 1(2010), 2 vom: 05. Okt., Seite 83-95 (DE-627)647305739 (DE-600)2595306-0 1869-5469 nnns volume:1 year:2010 number:2 day:05 month:10 pages:83-95 https://dx.doi.org/10.1007/s13278-010-0002-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 1 2010 2 05 10 83-95 |
| language |
English |
| source |
Enthalten in Social network analysis and mining 1(2010), 2 vom: 05. Okt., Seite 83-95 volume:1 year:2010 number:2 day:05 month:10 pages:83-95 |
| sourceStr |
Enthalten in Social network analysis and mining 1(2010), 2 vom: 05. Okt., Seite 83-95 volume:1 year:2010 number:2 day:05 month:10 pages:83-95 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Dynamic social networks Dynamic network visualization Clustering dynamic graphs Influence hierarchy in social networks |
| isfreeaccess_bool |
false |
| container_title |
Social network analysis and mining |
| authorswithroles_txt_mv |
Gilbert, Frédéric @@aut@@ Simonetto, Paolo @@aut@@ Zaidi, Faraz @@aut@@ Jourdan, Fabien @@aut@@ Bourqui, Romain @@aut@@ |
| publishDateDaySort_date |
2010-10-05T00:00:00Z |
| hierarchy_top_id |
647305739 |
| id |
SPR031180566 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR031180566</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230331070416.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2010 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s13278-010-0002-8</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR031180566</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13278-010-0002-8-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Gilbert, Frédéric</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Communities and hierarchical structures in dynamic social networks: analysis and visualization</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2010</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag 2010</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Dynamic social networks</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Dynamic network visualization</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Clustering dynamic graphs</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Influence hierarchy in social networks</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Simonetto, Paolo</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zaidi, Faraz</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jourdan, Fabien</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bourqui, Romain</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Social network analysis and mining</subfield><subfield code="d">Wien : Springer, 2011</subfield><subfield code="g">1(2010), 2 vom: 05. Okt., Seite 83-95</subfield><subfield code="w">(DE-627)647305739</subfield><subfield code="w">(DE-600)2595306-0</subfield><subfield code="x">1869-5469</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:1</subfield><subfield code="g">year:2010</subfield><subfield code="g">number:2</subfield><subfield code="g">day:05</subfield><subfield code="g">month:10</subfield><subfield code="g">pages:83-95</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s13278-010-0002-8</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">1</subfield><subfield code="j">2010</subfield><subfield code="e">2</subfield><subfield code="b">05</subfield><subfield code="c">10</subfield><subfield code="h">83-95</subfield></datafield></record></collection>
|
| author |
Gilbert, Frédéric |
| spellingShingle |
Gilbert, Frédéric misc Dynamic social networks misc Dynamic network visualization misc Clustering dynamic graphs misc Influence hierarchy in social networks Communities and hierarchical structures in dynamic social networks: analysis and visualization |
| authorStr |
Gilbert, Frédéric |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)647305739 |
| format |
electronic Article |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut |
| collection |
springer |
| remote_str |
true |
| illustrated |
Not Illustrated |
| issn |
1869-5469 |
| topic_title |
Communities and hierarchical structures in dynamic social networks: analysis and visualization Dynamic social networks (dpeaa)DE-He213 Dynamic network visualization (dpeaa)DE-He213 Clustering dynamic graphs (dpeaa)DE-He213 Influence hierarchy in social networks (dpeaa)DE-He213 |
| topic |
misc Dynamic social networks misc Dynamic network visualization misc Clustering dynamic graphs misc Influence hierarchy in social networks |
| topic_unstemmed |
misc Dynamic social networks misc Dynamic network visualization misc Clustering dynamic graphs misc Influence hierarchy in social networks |
| topic_browse |
misc Dynamic social networks misc Dynamic network visualization misc Clustering dynamic graphs misc Influence hierarchy in social networks |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
Social network analysis and mining |
| hierarchy_parent_id |
647305739 |
| hierarchy_top_title |
Social network analysis and mining |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)647305739 (DE-600)2595306-0 |
| title |
Communities and hierarchical structures in dynamic social networks: analysis and visualization |
| ctrlnum |
(DE-627)SPR031180566 (SPR)s13278-010-0002-8-e |
| title_full |
Communities and hierarchical structures in dynamic social networks: analysis and visualization |
| author_sort |
Gilbert, Frédéric |
| journal |
Social network analysis and mining |
| journalStr |
Social network analysis and mining |
| lang_code |
eng |
| isOA_bool |
false |
| recordtype |
marc |
| publishDateSort |
2010 |
| contenttype_str_mv |
txt |
| container_start_page |
83 |
| author_browse |
Gilbert, Frédéric Simonetto, Paolo Zaidi, Faraz Jourdan, Fabien Bourqui, Romain |
| container_volume |
1 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Gilbert, Frédéric |
| doi_str_mv |
10.1007/s13278-010-0002-8 |
| title_sort |
communities and hierarchical structures in dynamic social networks: analysis and visualization |
| title_auth |
Communities and hierarchical structures in dynamic social networks: analysis and visualization |
| abstract |
Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. © Springer-Verlag 2010 |
| abstractGer |
Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. © Springer-Verlag 2010 |
| abstract_unstemmed |
Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks. © Springer-Verlag 2010 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER |
| container_issue |
2 |
| title_short |
Communities and hierarchical structures in dynamic social networks: analysis and visualization |
| url |
https://dx.doi.org/10.1007/s13278-010-0002-8 |
| remote_bool |
true |
| author2 |
Simonetto, Paolo Zaidi, Faraz Jourdan, Fabien Bourqui, Romain |
| author2Str |
Simonetto, Paolo Zaidi, Faraz Jourdan, Fabien Bourqui, Romain |
| ppnlink |
647305739 |
| mediatype_str_mv |
c |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s13278-010-0002-8 |
| up_date |
2024-07-03T22:27:17.994Z |
| _version_ |
1803598574914633728 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR031180566</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230331070416.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2010 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s13278-010-0002-8</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR031180566</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s13278-010-0002-8-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Gilbert, Frédéric</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Communities and hierarchical structures in dynamic social networks: analysis and visualization</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2010</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag 2010</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individuals who play important roles in a society such as managers and decision makers. Detection and visualization of these networks that are changing over time is a challenging problem where communities change as a function of events taking place in the society and the role people play in it. In this paper, we address these issues by presenting a system to analyze dynamic social networks. The proposed system is based on dynamic graph discretization and graph clustering. The system allows detection of major structural changes taking place in social communities over time and reveals hierarchies by identifying influential people in social networks. We use two different data sets for the empirical evaluation and observe that our system helps to discover interesting facts about the social and hierarchical structures present in these social networks.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Dynamic social networks</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Dynamic network visualization</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Clustering dynamic graphs</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Influence hierarchy in social networks</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Simonetto, Paolo</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zaidi, Faraz</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jourdan, Fabien</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bourqui, Romain</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Social network analysis and mining</subfield><subfield code="d">Wien : Springer, 2011</subfield><subfield code="g">1(2010), 2 vom: 05. Okt., Seite 83-95</subfield><subfield code="w">(DE-627)647305739</subfield><subfield code="w">(DE-600)2595306-0</subfield><subfield code="x">1869-5469</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:1</subfield><subfield code="g">year:2010</subfield><subfield code="g">number:2</subfield><subfield code="g">day:05</subfield><subfield code="g">month:10</subfield><subfield code="g">pages:83-95</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s13278-010-0002-8</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">1</subfield><subfield code="j">2010</subfield><subfield code="e">2</subfield><subfield code="b">05</subfield><subfield code="c">10</subfield><subfield code="h">83-95</subfield></datafield></record></collection>
|
| score |
7.3982677 |