NetDriller-V3: A powerful social network analysis tool

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dc.authorid0000-0001-6657-9738
dc.contributor.authorAfra, Salim
dc.contributor.authorÖzyer, Tansel
dc.contributor.authorRokne, Jon
dc.contributor.authorAlhajj, Reda
dc.date.accessioned2023-04-26T09:28:59Z
dc.date.available2023-04-26T09:28:59Z
dc.date.issued2023
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractThe development in technology has led to the generation of huge amounts of data from various sources, including biological data, social networking data, etc. Accordingly, social network analysis has received considerable attention with the availability of more raw datasets which could be realized using a network structure. Most of the datasets can be represented as a social network which is a graph consisting of actors having relationships. Many tools exist for social network analysis inspired to extract knowledge from the networks. NetDriller has been developed as a social network extraction, manipulation and analysis tool to cover the lack that exists in other tools. It is capable of constructing social networks from raw data by employing a variety of data mining and machine learning techniques. In this paper, we describe an extend version of NetDriller, which has some new essential functions, including social network construction using data collection from Twitter, DBLP and IEEE. We also added (1) a new chart for viewing the network property and metrics, and (2) new graph manipulation techniques using GUI to keep the tool up to date with the huge volume of networks and the different types of raw data available on the web.
dc.identifier.citationAfra, S., Özyer, T., Rokne, J. ve Alhajj, R. (2023). NetDriller-V3: A powerful social network analysis tool. 14th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2022 içinde (570-574. ss.). Virtual, Online, 10-13 November 2022. https://dx.doi.org/10.1109/ASONAM55673.2022.10068570
dc.identifier.doi10.1109/ASONAM55673.2022.10068570
dc.identifier.endpage574
dc.identifier.isbn9781665456616
dc.identifier.scopus2-s2.0-85151930035
dc.identifier.scopusqualityN/A
dc.identifier.startpage570
dc.identifier.urihttps://dx.doi.org/10.1109/ASONAM55673.2022.10068570
dc.identifier.urihttps://hdl.handle.net/20.500.12511/10895
dc.indekslendigikaynakScopus
dc.institutionauthorAlhajj, Reda
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof14th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2022en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectData Mining
dc.subjectHierarchical Zooming
dc.subjectLink Prediction
dc.subjectMachine Learning
dc.subjectNetwork Construction
dc.subjectSocial Network Analysis
dc.titleNetDriller-V3: A powerful social network analysis tool
dc.typeConference Object

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