Loading…
Individual Neighbourhood Exploration in Complex Multi-layered Social Network
Social networks can be extracted from different data about communication or common activities in organizations, companies or various Internet-based services. Different types of data processed may result in creation of separate layers in the complex multilayered social network. Analysis of neighbourh...
Saved in:
Main Authors: | , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-a2493-5ee67043229858f5ec0ec3e7fc055ca1572129fb1f7f1dc4545bf4ff85b7d2bb3 |
---|---|
cites | |
container_end_page | 8 |
container_issue | |
container_start_page | 5 |
container_title | |
container_volume | 3 |
creator | Kazienko, Przemyslaw Brodka, Piotr Musial, Katarzyna |
description | Social networks can be extracted from different data about communication or common activities in organizations, companies or various Internet-based services. Different types of data processed may result in creation of separate layers in the complex multilayered social network. Analysis of neighbourhoods of network members and their utilization to social group discovery appears to be an interesting and important research domain. Since there is no measure to evaluate structure of the neighbourhoods in the multilayered social network, a new measure called cross layered multi-layered clustering coefficient (CLMCC) is proposed in the paper. It enables to analyse the density of mutual connections of neighbours that occur in at least a given number of layers in a social network. Additionally, experimental studies on real world data are presented. |
doi_str_mv | 10.1109/WI-IAT.2010.313 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>acm_6IE</sourceid><recordid>TN_cdi_ieee_primary_5614795</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5614795</ieee_id><sourcerecordid>acm_books_10_1109_WI_IAT_2010_313</sourcerecordid><originalsourceid>FETCH-LOGICAL-a2493-5ee67043229858f5ec0ec3e7fc055ca1572129fb1f7f1dc4545bf4ff85b7d2bb3</originalsourceid><addsrcrecordid>eNqNkD1PwzAURY0QEgg6M7BkZEnx80cdj1VVIFKBgaKOlu08U9O0rpIW2n9PSpmYmJ7uuzp3OIRcA-0DUH03K_NyOO0z2j048BPS06qgaqClAA3i9E8-J722_aCUAjAqZHFBJuWqip-x2to6e8b4Pndp28xTqrLxbl2nxm5iWmVxlY3Scl3jLnva1puY13aPDVbZa_Lxh9x8pWZxRc6CrVvs_d5L8nY_no4e88nLQzkaTnLLhOa5RBwoKjhjupBFkOgpeo4qeCqltyAVA6aDg6ACVF5IIV0QIRTSqYo5xy_JzXE3IqJZN3Fpm72RAxBKy67tH1vrl8altGgNUHPQZWal6XSZgy7T6TKuiRg64PafAP8G_Hdp8A</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Individual Neighbourhood Exploration in Complex Multi-layered Social Network</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Kazienko, Przemyslaw ; Brodka, Piotr ; Musial, Katarzyna</creator><creatorcontrib>Kazienko, Przemyslaw ; Brodka, Piotr ; Musial, Katarzyna</creatorcontrib><description>Social networks can be extracted from different data about communication or common activities in organizations, companies or various Internet-based services. Different types of data processed may result in creation of separate layers in the complex multilayered social network. Analysis of neighbourhoods of network members and their utilization to social group discovery appears to be an interesting and important research domain. Since there is no measure to evaluate structure of the neighbourhoods in the multilayered social network, a new measure called cross layered multi-layered clustering coefficient (CLMCC) is proposed in the paper. It enables to analyse the density of mutual connections of neighbours that occur in at least a given number of layers in a social network. Additionally, experimental studies on real world data are presented.</description><identifier>ISBN: 9780769541914</identifier><identifier>ISBN: 0769541917</identifier><identifier>ISBN: 9781424484829</identifier><identifier>ISBN: 1424484820</identifier><identifier>EISBN: 9780769541914</identifier><identifier>EISBN: 0769541917</identifier><identifier>DOI: 10.1109/WI-IAT.2010.313</identifier><language>eng</language><publisher>Washington, DC, USA: IEEE Computer Society</publisher><subject>Communication channels ; Complex networks ; Cross layer design ; Fitting ; Mathematics of computing ; Mathematics of computing -- Discrete mathematics ; Mathematics of computing -- Discrete mathematics -- Graph theory ; Mathematics of computing -- Discrete mathematics -- Graph theory -- Network flows ; Measurement ; multi-layered social network ; neighbourhood analysis ; Presses ; social network analysis ; Social network services</subject><ispartof>2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2010, Vol.3, p.5-8</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a2493-5ee67043229858f5ec0ec3e7fc055ca1572129fb1f7f1dc4545bf4ff85b7d2bb3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5614795$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5614795$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Kazienko, Przemyslaw</creatorcontrib><creatorcontrib>Brodka, Piotr</creatorcontrib><creatorcontrib>Musial, Katarzyna</creatorcontrib><title>Individual Neighbourhood Exploration in Complex Multi-layered Social Network</title><title>2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology</title><addtitle>wi-iat</addtitle><description>Social networks can be extracted from different data about communication or common activities in organizations, companies or various Internet-based services. Different types of data processed may result in creation of separate layers in the complex multilayered social network. Analysis of neighbourhoods of network members and their utilization to social group discovery appears to be an interesting and important research domain. Since there is no measure to evaluate structure of the neighbourhoods in the multilayered social network, a new measure called cross layered multi-layered clustering coefficient (CLMCC) is proposed in the paper. It enables to analyse the density of mutual connections of neighbours that occur in at least a given number of layers in a social network. Additionally, experimental studies on real world data are presented.</description><subject>Communication channels</subject><subject>Complex networks</subject><subject>Cross layer design</subject><subject>Fitting</subject><subject>Mathematics of computing</subject><subject>Mathematics of computing -- Discrete mathematics</subject><subject>Mathematics of computing -- Discrete mathematics -- Graph theory</subject><subject>Mathematics of computing -- Discrete mathematics -- Graph theory -- Network flows</subject><subject>Measurement</subject><subject>multi-layered social network</subject><subject>neighbourhood analysis</subject><subject>Presses</subject><subject>social network analysis</subject><subject>Social network services</subject><isbn>9780769541914</isbn><isbn>0769541917</isbn><isbn>9781424484829</isbn><isbn>1424484820</isbn><isbn>9780769541914</isbn><isbn>0769541917</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNqNkD1PwzAURY0QEgg6M7BkZEnx80cdj1VVIFKBgaKOlu08U9O0rpIW2n9PSpmYmJ7uuzp3OIRcA-0DUH03K_NyOO0z2j048BPS06qgaqClAA3i9E8-J722_aCUAjAqZHFBJuWqip-x2to6e8b4Pndp28xTqrLxbl2nxm5iWmVxlY3Scl3jLnva1puY13aPDVbZa_Lxh9x8pWZxRc6CrVvs_d5L8nY_no4e88nLQzkaTnLLhOa5RBwoKjhjupBFkOgpeo4qeCqltyAVA6aDg6ACVF5IIV0QIRTSqYo5xy_JzXE3IqJZN3Fpm72RAxBKy67tH1vrl8altGgNUHPQZWal6XSZgy7T6TKuiRg64PafAP8G_Hdp8A</recordid><startdate>20100831</startdate><enddate>20100831</enddate><creator>Kazienko, Przemyslaw</creator><creator>Brodka, Piotr</creator><creator>Musial, Katarzyna</creator><general>IEEE Computer Society</general><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20100831</creationdate><title>Individual Neighbourhood Exploration in Complex Multi-layered Social Network</title><author>Kazienko, Przemyslaw ; Brodka, Piotr ; Musial, Katarzyna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a2493-5ee67043229858f5ec0ec3e7fc055ca1572129fb1f7f1dc4545bf4ff85b7d2bb3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Communication channels</topic><topic>Complex networks</topic><topic>Cross layer design</topic><topic>Fitting</topic><topic>Mathematics of computing</topic><topic>Mathematics of computing -- Discrete mathematics</topic><topic>Mathematics of computing -- Discrete mathematics -- Graph theory</topic><topic>Mathematics of computing -- Discrete mathematics -- Graph theory -- Network flows</topic><topic>Measurement</topic><topic>multi-layered social network</topic><topic>neighbourhood analysis</topic><topic>Presses</topic><topic>social network analysis</topic><topic>Social network services</topic><toplevel>online_resources</toplevel><creatorcontrib>Kazienko, Przemyslaw</creatorcontrib><creatorcontrib>Brodka, Piotr</creatorcontrib><creatorcontrib>Musial, Katarzyna</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kazienko, Przemyslaw</au><au>Brodka, Piotr</au><au>Musial, Katarzyna</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Individual Neighbourhood Exploration in Complex Multi-layered Social Network</atitle><btitle>2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology</btitle><stitle>wi-iat</stitle><date>2010-08-31</date><risdate>2010</risdate><volume>3</volume><spage>5</spage><epage>8</epage><pages>5-8</pages><isbn>9780769541914</isbn><isbn>0769541917</isbn><isbn>9781424484829</isbn><isbn>1424484820</isbn><eisbn>9780769541914</eisbn><eisbn>0769541917</eisbn><abstract>Social networks can be extracted from different data about communication or common activities in organizations, companies or various Internet-based services. Different types of data processed may result in creation of separate layers in the complex multilayered social network. Analysis of neighbourhoods of network members and their utilization to social group discovery appears to be an interesting and important research domain. Since there is no measure to evaluate structure of the neighbourhoods in the multilayered social network, a new measure called cross layered multi-layered clustering coefficient (CLMCC) is proposed in the paper. It enables to analyse the density of mutual connections of neighbours that occur in at least a given number of layers in a social network. Additionally, experimental studies on real world data are presented.</abstract><cop>Washington, DC, USA</cop><pub>IEEE Computer Society</pub><doi>10.1109/WI-IAT.2010.313</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISBN: 9780769541914 |
ispartof | 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2010, Vol.3, p.5-8 |
issn | |
language | eng |
recordid | cdi_ieee_primary_5614795 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Communication channels Complex networks Cross layer design Fitting Mathematics of computing Mathematics of computing -- Discrete mathematics Mathematics of computing -- Discrete mathematics -- Graph theory Mathematics of computing -- Discrete mathematics -- Graph theory -- Network flows Measurement multi-layered social network neighbourhood analysis Presses social network analysis Social network services |
title | Individual Neighbourhood Exploration in Complex Multi-layered Social Network |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T23%3A30%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-acm_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Individual%20Neighbourhood%20Exploration%20in%20Complex%20Multi-layered%20Social%20Network&rft.btitle=2010%20IEEE/WIC/ACM%20International%20Conference%20on%20Web%20Intelligence%20and%20Intelligent%20Agent%20Technology&rft.au=Kazienko,%20Przemyslaw&rft.date=2010-08-31&rft.volume=3&rft.spage=5&rft.epage=8&rft.pages=5-8&rft.isbn=9780769541914&rft.isbn_list=0769541917&rft.isbn_list=9781424484829&rft.isbn_list=1424484820&rft_id=info:doi/10.1109/WI-IAT.2010.313&rft.eisbn=9780769541914&rft.eisbn_list=0769541917&rft_dat=%3Cacm_6IE%3Eacm_books_10_1109_WI_IAT_2010_313%3C/acm_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a2493-5ee67043229858f5ec0ec3e7fc055ca1572129fb1f7f1dc4545bf4ff85b7d2bb3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5614795&rfr_iscdi=true |