Social networks data mining using visual analytics

dc.contributor.author	Ξύδας, Ιωάννης	el
dc.contributor.author	Νικολοπούλου, Νάντια	el
dc.contributor.author	Μιαούλης, Γεώργιος	el
dc.date.accessioned	2015-05-08T08:43:59Z
dc.date.available	2015-05-08T08:43:59Z
dc.date.issued	2015-05-08
dc.identifier.uri	http://hdl.handle.net/11400/9923
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://3ia.teiath.gr/	en
dc.source	http://users.teiath.gr/yxydas/Paper4_xydas.pdf	en
dc.subject	Social Networks
dc.subject	Data Mining
dc.subject	Social Network Data Mining
dc.subject	Visual analytics
dc.subject	Social Network Visualization
dc.subject	Twitter Visualization
dc.subject	Κοινωνικά δίκτυα
dc.subject	Εξόρυξη δεδομένων
dc.subject	Εξόρυξη δεδομένων από κοινωνικά δίκτυα
dc.subject	Οπτική αναλυτική
dc.subject	Απεικόνιση δεδομένων κοινωνικών δικτύων
dc.subject	Απεικόνιση δεδομένων twitter
dc.title	Social networks data mining using visual analytics	en
heal.type	conferenceItem
heal.classification	Technology
heal.classification	Computer science
heal.classification	Τεχνολογία
heal.classification	Πληροφορική
heal.classificationURI	http://zbw.eu/stw/descriptor/10470-6
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Πληροφορική
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh2007004134
heal.identifier.secondary	ISBN: 2-914256-13-2
heal.language	en
heal.access	free
heal.recordProvider	Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε.	el
heal.publicationDate	2011-05
heal.bibliographicCitation	Nikolopoulou, K., Xydas, I. and Miaoulis, G. (2011) Social networks data mining using visual analytics. In "31A International Conference on Computer Graphics and Artificial Intelligence". Athens: Technological Educational Institute of Athens. Available from: http://users.teiath.gr/yxydas/Paper4_xydas.pdf [Accessed: 08/05/2015].	en
heal.abstract	Internet - based social networks are facilities (typically web sites) where people can form online communities, connect to each other and share information. This paper explores the are a of applying visual analytics to represent data and underlying relationships in social networks – more specifically, on the Twitter micro - blogging service. Networks of this kind can be treated as graphs, where each node corresponds to a user or a specific piece of information and edges connect such nodes representing relationships. Visualizing graphs is a vast research area i n its own right, with numerous applications in science and engineering. In this assignment we are using readily - available software to visualize parts of the network , via filtering or other operations, in order to be able to draw conclusions . Social networks are an excellent candidate to apply visual analytics to , due to their exponential growth when new users join	en
heal.publisher	Technological Educational Institute of Athens	en
heal.publisher	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας	el
heal.fullTextAvailability	true
heal.conferenceName	31A International Conference on Computer Graphics and Artificial Intelligence	en
heal.conferenceItemType	full paper