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     <dc:title xml:lang="fr">Détection de fausses informations dans les réseaux sociaux</dc:title>
     <dcterms:alternative xml:lang="en">Detection of misleading information on social networks</dcterms:alternative>
     <dc:subject xml:lang="fr">fausses informations</dc:subject><dc:subject xml:lang="fr">réseaux sociaux</dc:subject><dc:subject xml:lang="fr">crédibilité de la source</dc:subject><dc:subject xml:lang="fr">traitement des langues</dc:subject><dc:subject xml:lang="fr">analyse du signal
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     <dc:subject xml:lang="en">false information</dc:subject><dc:subject xml:lang="en">social networks</dc:subject><dc:subject xml:lang="en">source trustworthiness</dc:subject><dc:subject xml:lang="en">natural language processing</dc:subject><dc:subject xml:lang="en">signal analysis</dc:subject><tef:sujetRameau><tef:vedetteRameauNomCommun>
						<tef:elementdEntree autoriteSource="Sudoc" autoriteExterne="035063823">Diffusion d'informations fausses et trompeuses</tef:elementdEntree>
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						<tef:elementdEntree autoriteSource="Sudoc" autoriteExterne="22621768X">Infox</tef:elementdEntree>
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						<tef:elementdEntree autoriteSource="Sudoc" autoriteExterne="103427961">Réseaux sociaux (Internet)</tef:elementdEntree>
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						<tef:elementdEntree autoriteSource="Sudoc" autoriteExterne="027253287">Traitement du signal</tef:elementdEntree>
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						<tef:elementdEntree autoriteSource="Sudoc" autoriteExterne="027673618">Traitement d'images -- Techniques numériques</tef:elementdEntree>
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     <dcterms:abstract xml:lang="fr">Les fausses informations se multiplient et se propagent rapidement sur les réseaux sociaux. Dans cette thèse, nous analysons les publications d’un point de vue multimodal entre le texte et l’image associée. Plusieurs études ont été menées durant cette thèse. La première compare plusieurs types de médias présents sur les réseaux sociaux et vise à les discriminer de manière automatique. La second permet la détection et la localisation de modiﬁcations dans une image grâce à la comparaison avec une ancienne version de l’image. Enﬁn, nous nous sommes intéressés à des fusions de connaissances basées sur les prédictions d’autres équipes de recherche aﬁn de créer un système unique.</dcterms:abstract>
     <dcterms:abstract xml:lang="en">False information are multiplying and are spreading quickly on social networks. In this thesis, we analyze the publications from a multimodal point of view between the text and the associated image. Several studies were conducted during this thesis. The ﬁrst compares several types of media present on social networks and aims to discriminate them automatically. The second one allows the detection and the localization of modiﬁcations in an image thanks to the comparison with an old version of this image. Finally, we focused on merged knowledge based on the predictions of other research teams to create a single system.</dcterms:abstract>
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