Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/7066
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dc.contributor.authorKarataş, Arzum-
dc.contributor.authorŞahin, Serap-
dc.date.accessioned2018-12-25T07:08:25Z-
dc.date.available2018-12-25T07:08:25Z-
dc.date.issued2018-
dc.identifier.citationKarataş, A., and Şahin, S. (2018, September 10-12). A comparative study of modularity-based community detection methods for online social networks. In A. Tarhan and Murat E. (Eds.), paper presented at the 12th Turkish National Software Engineering Symposium, UYMS 2018; Istanbul; Turkey.en_US
dc.identifier.issn1613-0073-
dc.identifier.urihttp://ceur-ws.org/Vol-2201/UYMS_2018_paper_68.pdf-
dc.identifier.urihttp://hdl.handle.net/11147/7066-
dc.description12th Turkish National Software Engineering Symposium, UYMS 2018; Istanbul; Turkey; 10 September 2018 through 12 September 2018en_US
dc.description.abstractDigital data represent our daily activities and tendencies. One of its main source is Online Social Networks (OSN) such as Facebook, YouTube etc. OSN are generating continuously high volume of data and define a dynamic virtual environment. This environment is mostly represented by graphs. Analysis of OSN data (i.e.,extracting any kind of relations and tendencies) defines valuable information for economic, socio-cultural and politic decisions. Community detection is important to analyze and understand underlying structure and tendencies of OSNs. When this information can be analysed successfully, software engineering tools and decision support systems can produce more successful results for end users. In this study, we present a survey of selected outstanding modularity-based static community detection algorithms and do comparative analysis among them in terms of modularity, running time and accuracy. We use different real-world OSN test beds selected from SNAP dataset collection such as Facebook Ego network, Facebook Pages network (Facebook gemsec), LiveJournal, Orkut and YouTube networks.en_US
dc.language.isoenen_US
dc.publisherCEUR Workshop Proceedingsen_US
dc.relation.ispartof12th Turkish National Software Engineering Symposium, UYMS 2018en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCommunity detectionen_US
dc.subjectOnline Social Networken_US
dc.subjectModularityen_US
dc.subjectSocial network analysisen_US
dc.titleA comparative study of modularity-based community detection methods for online social networksen_US
dc.title.alternativeÇevrimiçi sosyal ağlar İçin modülerite tabanlı topluluk algılama yöntemlerinin karşılaştırmalı bir çalışmasıen_US
dc.typeConference Objecten_US
dc.authoridTR115373en_US
dc.institutionauthorKarataş, Arzum-
dc.institutionauthorŞahin, Serap-
dc.departmentİzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.volume2201en_US
dc.identifier.scopus2-s2.0-85053710404en_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - Kurum Öğretim Elemanıen_US
dc.identifier.scopusquality--
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairetypeConference Object-
crisitem.author.dept03.04. Department of Computer Engineering-
crisitem.author.dept03.04. Department of Computer Engineering-
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Sürdürülebilir Yeşil Kampüs Koleksiyonu / Sustainable Green Campus Collection
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