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Narration and direct‐to‐camera monologues were analysed through frequency counts. The final aim was to outline how these findings can inform the actions of nurses, nursing organizations and writers and journalists.Ĭharacter network analysis was used to describe the verbal interaction of nurses and doctors and identify major, minor and background characters. The aim of this study was to describe how nurses' dialogue compares with that of doctors in the Australian reality television program Emergency and to explain how this dialogue and the use of narration and direct‐to‐camera monologues contribute to the portrayal of nurses. KeywordsCharacter-net–Character–Movie–Community clustering–Story-based–Social network Our experiments show that our proposed method can efficiently detect sequences. Via clustering communities composed of characters. To achieve this, we proposeĪ Character-net that can represent the relationships between characters using dialogs, and a method that can extract the sequences

Additionally, through social networks using the dialog, we can extract accurate movie stories suchĪs classification of major, minor or extra roles, community clustering, and sequence detection. Therefore, the dialog is better for constructing social networks of characters A dialog hasĪ direction and time that supplies information.

Progression of most movie stories is done by characters,Īnd the scriptwriter or director narrates the story and relationships among characters using character dialogs. Therefore, through social network analysis among characters, movie story information suchĪs the major roles and the corresponding communities can be determined. Various types of information retrieval better than audio-visual feature analysis. Movie analysis through social relationships among characters can support Means to extract semantic information from movies. There have been various approaches to analyzing movie stories using social networks.

The social network watch online subtitles