A Comparative Study of Modularity-Based Community Detection Methods for Online Social Networks
| dc.contributor.author | Karataş, Arzum | |
| dc.contributor.author | Şahin, Serap | |
| dc.contributor.other | 03.04. Department of Computer Engineering | |
| dc.contributor.other | 03. Faculty of Engineering | |
| dc.contributor.other | 01. Izmir Institute of Technology | |
| dc.date.accessioned | 2018-12-25T07:08:25Z | |
| dc.date.available | 2018-12-25T07:08:25Z | |
| dc.date.issued | 2018 | |
| dc.description | 12th Turkish National Software Engineering Symposium, UYMS 2018; Istanbul; Turkey; 10 September 2018 through 12 September 2018 | en_US |
| dc.description.abstract | Digital 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.identifier.citation | Karataş, 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.issn | 1613-0073 | |
| dc.identifier.scopus | 2-s2.0-85053710404 | |
| dc.identifier.uri | http://ceur-ws.org/Vol-2201/UYMS_2018_paper_68.pdf | |
| dc.identifier.uri | http://hdl.handle.net/11147/7066 | |
| dc.language.iso | en | en_US |
| dc.publisher | CEUR Workshop Proceedings | en_US |
| dc.relation.ispartof | 12th Turkish National Software Engineering Symposium, UYMS 2018 | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Community detection | en_US |
| dc.subject | Online Social Network | en_US |
| dc.subject | Modularity | en_US |
| dc.subject | Social network analysis | en_US |
| dc.title | A Comparative Study of Modularity-Based Community Detection Methods for Online Social Networks | en_US |
| dc.title.alternative | Çevrimiçi Sosyal Ağlar İçin Modülerite Tabanlı Topluluk Algılama Yöntemlerinin Karşılaştırmalı Bir Çalışması | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
| gdc.author.id | TR115373 | |
| gdc.author.institutional | Karataş, Arzum | |
| gdc.author.institutional | Karataş, Arzum | |
| gdc.author.institutional | Şahin, Serap | |
| gdc.coar.access | open access | |
| gdc.coar.type | text::conference output | |
| gdc.description.department | İzmir Institute of Technology. Computer Engineering | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Ulusal - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q4 | |
| gdc.description.volume | 2201 | en_US |
| gdc.description.wosquality | N/A | |
| gdc.scopus.citedcount | 2 | |
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