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Extraction de réseaux dynamiques conversationnels par lissage narratif

Abstract : Modern TV series tend to develop complex, multiple, parallel plots, spanning several seasons. However, they are typically watched on a very short time period. Viewers therefore sometimes feel the need to consult a summary before watching a new season. However, such summaries are generally produced manually, which is expensive. This work is the first step in the proposition of an automatic summarization method. We model the plot of a modern TV series through the dynamic conversational network of its characters. Instead of aggregating these relations over the whole considered period or over a sequence of time windows, we propose narrative smoothing, a new approach more appropriate to the complex plots of such series. It automatically determines the temporal scale of the network based on the dynamics of the character interactions. We present the preliminary results obtained on three popular current series: Breaking Bad, Game of Thrones and House of Cards.
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Contributor : Vincent Labatut <>
Submitted on : Monday, October 24, 2016 - 5:10:56 PM
Last modification on : Thursday, July 15, 2021 - 9:04:01 AM


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  • HAL Id : hal-01385215, version 1



Xavier Bost, Vincent Labatut, Serigne Gueye, Georges Linarès. Extraction de réseaux dynamiques conversationnels par lissage narratif. 7ème Conférence Modèles & Analyse de Réseaux : approches mathématiques et informatiques (MARAMI), Oct 2016, Cergy-Pontoise, France. ⟨hal-01385215⟩



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