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Predicting social networks in weblogs

dc.contributor.authorJähnichen, Patrick
dc.contributor.editorEichler, Gerald
dc.contributor.editorKüpper, Axel
dc.contributor.editorSchau, Volkmar
dc.contributor.editorFouchal, Hacène
dc.contributor.editorUnger, Herwig
dc.contributor.editorEichler, Gerald
dc.contributor.editorKüpper, Axel
dc.contributor.editorSchau, Volkmar
dc.contributor.editorFouchal, Hacène
dc.contributor.editorUnger, Herwig
dc.date.accessioned2019-01-11T09:29:07Z
dc.date.available2019-01-11T09:29:07Z
dc.date.issued2011
dc.description.abstractWeblogs and other platforms used to organize a social life online have achieved an enormous success over the last few years. Opposed to applications directly designed for building up and visualizing social networks, weblogs are comprised of mostly unstructured text data, that comes with some meta data, such as the author of the text, its publication date or the URL it is available under. In this paper, we propose a way, how these networks may be inferred not by the available meta data, but by pure natural language analysis of the text content, allowing inference of these networks without any meta data at hand. We discuss results of first experiments and outline possible enhancements as well as other ways to improve prediction of social networks based solely on content analysis.en
dc.identifier.isbn978-3-88579-280-2
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/18999
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof11th International Conference on Innovative Internet Community Systems (I2CS 2011)
dc.relation.ispartof11th International Conference on Innovative Internet Community Systems (I2CS 2011)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-186
dc.titlePredicting social networks in weblogsen
dc.typeText/Conference Paper
gi.citation.endPage47
gi.citation.publisherPlaceBonn
gi.citation.startPage38
gi.conference.dateJune 15-17, 2011
gi.conference.locationBerlin
gi.conference.sessiontitleRegular Research Papers

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