Document (#35638)

Author
Knautz, K.
Dröge, E.
Finkelmeyer, S.
Guschauski, D.
Juchem, K.
Krzmyk, C.
Miskovic, D.
Schiefer, J.
Sen, E.
Verbina, J.
Werner, N.
Stock, W.G.
Title
Indexieren von Emotionen bei Videos
Source
Information - Wissenschaft und Praxis. 61(2010) H.4, S.221-236
Year
2010
Abstract
Gegenstand der empirischen Forschungsarbeit sind dargestellte wie empfundene Gefühle bei Videos. Sind Nutzer in der Lage, solche Gefühle derart konsistent zu erschließen, dass man deren Angaben für ein emotionales Videoretrieval gebrauchen kann? Wir arbeiten mit einem kontrollierten Vokabular für neun tionen (Liebe, Freude, Spaß, Überraschung, Sehnsucht, Trauer, Ärger, Ekel und Angst), einem Schieberegler zur Einstellung der jeweiligen Intensität des Gefühls und mit dem Ansatz der broad Folksonomy, lassen also unterschiedliche Nutzer die Videos taggen. Versuchspersonen bekamen insgesamt 20 Videos (bearbeitete Filme aus YouTube) vorgelegt, deren Emotionen sie indexieren sollten. Wir erhielten Angaben von 776 Probanden und entsprechend 279.360 Schiebereglereinstellungen. Die Konsistenz der Nutzervoten ist sehr hoch; die Tags führen zu stabilen Verteilungen der Emotionen für die einzelnen Videos. Die endgültige Form der Verteilungen wird schon bei relativ wenigen Nutzern (unter 100) erreicht. Es ist möglich, im Sinne der Power Tags die jeweils für ein Dokument zentralen Gefühle (soweit überhaupt vorhanden) zu separieren und für das emotionale Information Retrieval (EmIR) aufzubereiten.
Theme
Benutzerstudien
Inhaltsanalyse
Form
Videos

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