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  • Digital Humanities and Cultural Heritage
  • 2017-2021
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  • Authors: Torres Aguilar, Sergio; Stutzmann, Dominique;

    International audience; This paper presents the process of annotating and modelling a corpus to automatically detect named entities in medieval charters in French. It introduces a new annotated corpus and a new system which outperforms state-of-the art libraries. Charters are legal documents and among the most important historical sources for medieval studies as they reflect economic and social dynamics as well as the evolution of literacy and writing practices. Automatic detection of named entities greatly improves the access to these unstructured texts and facilitates historical research. The experiments described here are based on a corpus encompassing about 500k words (1200 charters) coming from three charter collections ofthe 13th and 14th centuries. We annotated the corpus and then trained two state-of-the art NLP libraries for Named Entity Recognition (Spacy and Flair) and a custom neural model (Bi-LSTM-CRF). The evaluation shows that all three models achieve a high performance rate on the test set and a high generalization capacity against two external corpora unseen during training. This paper describes the corpus and the annotation model, and discusses the issues related to the linguistic processing of medieval French and formulaic discourse, so as to interpret the results within a larger historical perspective.

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    Authors: Vorakitphan, Vorakit;

    La désinformation, dont la propagation s’est accentuée par le biais des médias sociaux, suscite aujourd’hui une réelle menace pour la société. Il existe différents moyens de véhiculer de la désinformation, par exemple par le biais de contenus délibérément manipulés ou fabriqués dans le but de créer des théories conspirationnistes, de rumeurs ou encore de positions et jugements erronés, tels que l’on peut en rencontrer dans des articles d'actualité, discours et débats politiques. L'une des nombreuses formes de désinformation rencontrée en ligne, et certainement l'une des plus dangereuses, est la propagande. Ce type de désinformation, que l’on retrouve notamment en politique, représente une stratégie de communication efficace mais souvent trompeuse utilisée pour promouvoir un certain point de vue auprès du public. La nécessité d'identifier, de classifier et de comprendre efficacement et automatiquement ce type de phénomène devient pressant. Dans cette thèse, j'aborde cette question et je propose une approche de classification fine des textes polarisés et de propagande issus d’articles de presse et de débats politiques. Selon le sujet abordé, le contexte, la source d'information, les antécédents et les préférences constituent un panel de facteurs pouvant influer sur les perceptions de l’auditoire et donc conduire à sa déviation ou polarisation en faveur d’un parti. À partir d’un cas d’utilisation provenant d’un scénario politique, nous proposons d’explorer les impacts d’une telle polarisation par le biais de méthodes issues de l’analyse de sentiment basée sur des aspects. L’objectif étant de vérifier dans quelle mesure ces méthodes peuvent permettre d’obtenir des informations sur les messages politiques postés sur les médias sociaux. Plus particulièrement, la thèse traite de la conception et de l'évaluation d'un certain nombre de techniques d'extraction des principales caractéristiques des textes de propagande dans le domaine du Traitement Automatique du Langage Naturel (TALN). L'analyse de sentiment, les techniques de persuasion, la simplicité des messages et l'argumentation y sont notamment proposées et étudiées en profondeur. Les résultats de cette thèse montrent que ces caractéristiques peuvent capturer des propriétés particulières permettant de caractériser la propagande dans les textes. D’autre part, ces caractéristiques sont employées dans le cadre de la conception et l'implémentation d'une architecture neuronale ayant pour vocation à détecter et classifier les techniques de propagande à grain fin. Le travail proposé dans cette thèse va au-delà de l'état de l'art des systèmes actuels de détection et de classification de la propagande à grain fin. En effet, plusieurs approches d'apprentissage automatique, allant de la régression logistique à des architectures neuronales récentes, ont été testées sur des jeux de données standard de détection de la propagande. En conséquence, un pipeline complet de détection et de classification de la propagande est présenté. La tâche de détection des extraits de textes de propagande a obtenu un score F1 de 0,71, et l'architecture basée sur les transformateurs a obtenu une moyenne de 0,67 pour la tâche de classification des techniques de propagande, surpassant ainsi les systèmes de pointe. Ce pipeline est démontré avec un outil de preuve de concept appelé PROTECT. Enfin, comme dernière contribution de cette thèse, j'ai participé à la création d'une nouvelle ressource linguistique annotée. Composée de textes issus des débats politiques des campagnes présidentielles américaines de 1960 à 2016, cette ressource est annotée avec 6 types de techniques de propagande qui se décomposent en 14 sous-catégories de propagande. L'ensemble de données que j'ai construit contient 1666 instances de propagande. In recent years, disinformation has become more viral, mainly due to its spread online on social media, leading to potential threatening consequences for the society. Heterogeneous forms of online disinformation are possible, i.e., deliberately manipulated or fabricated content with the intentional aim of creating conspiracy theories, rumours, or misbehaved stances and judgements, for instance, in news articles, and political discourse and debates. One of many instances of online disinformation, and certainly one of the most dangerous ones, is propaganda. This disinformation instance represents an effective but often misleading communication strategy which is employed to promote a certain viewpoint to the audience, for instance in the political context. The need to effectively and automatically identify, classify and understand such phenomenon is becoming a urgent need. In this thesis, I tackle this issue and I propose a fine-grained classification approach of polarized and propagandist text in news articles and political debates. More precisely, as the audience' perceptions are perceived differently depending on the context, the source of information, the audience background and preferences, a discussed topic can deviate or polarize the audience into a partisanship. This thesis firstly investigates such polarization given a use-case in a political scenario using Aspects-Based Sentiment Analysis to verify how extensively these methods can be employed to gain insights from the political posts on social media. The thesis discusses the design and evaluation of a number of techniques in extracting the main features of propagandist text in the area of Natural Language Processing (NLP) where sentiment analysis, persuasion techniques, message simplicity, and ultimately argumentation are proposed and thoroughly investigated. The findings in this thesis show that such features can capture particular characteristics of propaganda in texts. Furthermore, these features are employed to tackle the NLP tasks of propaganda detection and classification through the design and implementation of a neural architecture to classify fine-grained propaganda techniques. The work in this thesis goes beyond the state-of-the-art of current systems for fine-grained propaganda detection and classification. Various Machine Learning approaches ranging from feature-based logistic regression to recent neural architectures have been experimented on standard benchmarks in propaganda detection. As a result, a full pipeline in propaganda detection and classification is presented where the task of detecting the propagandist text snippets obtained .71 F1-score, and the transformer-based architecture obtained an average of .67 F1-score for the task of propaganda technique classification, outperforming the state-of-the-art systems. This pipeline is demonstrated with a proof-of-concept tool called PROTECT. Finally, as a last contribution of this thesis, I carried out the creation of a new annotated linguistic resource. This resource is annotated with 6 types of propaganda techniques, which breaks down into 14 sub-categories of propaganda in the political debates of the US presidential campaigns from 1960 to 2016. The data set I built contains 1666 instances of propagandist text.

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    Authors: Ferrari, Erika;

    Le patrimoine métallique est un témoin culturel de notre passé et, pour cette raison, sa préservation et sa transmission aux générations futures sont importantes. Plusieurs stratégies sont utilisées pour la protection du patrimoine cuivreux exposée en extérieur, dont l’utilisation des inhibiteurs de corrosion organiques. Les inhibiteurs utilisés pour le patrimoine sont généralement empruntés au domaine de l’industrie. Cependant, l’état de surface du métal, couvert par des couches de produits de corrosion complexes, et le protocole d’application des inhibiteurs diffèrent considérablement de l’application industrielle.La présente étude porte spécifiquement sur les inhibiteurs de corrosion pour la conservation des artefacts exposés à base de cuivre par une approche physico-chimique innovante. L'approche prend en compte la complexité de la couche de corrosion étudiée : une plaque de cuivre naturellement corrodée, représentative de la corrosion extérieure à long terme a été choisie. Pour l'étude, trois molécules organiques, caractérisées par des fonctions chimiques différentes ont été sélectionnées comme inhibiteurs de test : le benzotriazole (BTAH), un composé azolé, employé en conservation, dont l'efficacité est débattue et l’utilisation déconseillée en raison de sa toxicité ; l'acide décanoïque (HC10) un acide gras à longue chaîne qui a été proposé comme traitement pour les objets patrimoniaux ; l'acide benzotriazole-5-carboxylique (5CBT), un composé à fonctions mixtes azole-carboxyliques. La réactivité des inhibiteurs avec des phases minérales synthétiques représentatives des produits de corrosion ainsi que des échantillons corrodés anciens (100 ans) avant et après 6 mois d'exposition extérieure ont été étudiées en combinant des observations à l'échelle nanométrique (MET, FIB-tomographie) à celles obtenues à l'échelle microscopique (Raman, MEB-EDS) et des observations globales/globales (couleur, tension de surface, XRD). Des expériences complémentaires en milieux marqués ont permis d'étudier les évolutions de perméabilité (immersion en D₂O) et de comportement passif (immersion KBr). Deux mécanismes réactionnels ont été observés et une relation avec l'efficacité et la durabilité de l'inhibition est proposée. Les molécules caractérisées par la fonction azole (BTAH et 5CBT) réagissent selon un mécanisme d'adsorption-précipitation formant un complexe amorphe adsorbé (film nanométrique) sur la phase minérale substrat (cuprite et brochantite). Les deux traitements sur les couches anciennes de corrosion diffèrent par leur profondeur de pénétration, la formation du complexe BTAH étant détectée jusqu'à la couche interne de cuprite, tandis que la complexation 5CBT n'est observée que dans la partie externe de la brochantite. Ceci a un impact sur la perméabilité de l'eau et la passivité pour les traitements au BTAH qui montrent les meilleurs résultats, et suggère une formation de complexe Cu-BTA sur la partie externe de la couche de cuprite dans ce dernier traitement. La fonction carboxylique dans HC10 conduit à la précipitation du décanoate de cuivre par un mécanisme de dissolution-précipitation. Des cristaux de décanoate se forment sur la surface externe de brochantite : cela confère une quasi-superhydrophobie à l'échantillon après traitement. Cependant, le manque de liaison chimique forte entre le précipité et la surface induit la perte de la couche hydrophobe déposée en surface après 6 mois d'exposition à l'extérieur.En plus de ces résultats phénoménologiques, une nouvelle méthodologie basée sur l'expérience KBr pour tester les inhibiteurs des artefacts corrodés par le cuivre est également proposée. Metallic heritage artefacts represent cultural traces of our past, and for this reason, their preservation and transmission to future generations is important. To protect copper-based artworks exposed outdoors, several conservation strategies are followed, including the use of organic corrosion inhibitors. Inhibitors are usually borrowed from the industrial field. However, the surface state of the metal with the presence of complex corrosion layers, and the protocol of inhibitors' application differ considerably from the industrial ones.The present study specifically addresses corrosion inhibitors for conservation of copper-based exposed artifacts by an innovative physico-chemical approach. The approach takes into account the complexity of the corrosion layer under investigation: a naturally corroded copper plate, representative for outdoor long-term corrosion have been chosen. For the study, three organic molecules, characterized by different chemical functions have been selected as test inhibitors: benzotriazole (BTAH), an azole compound, employed in conservation, which efficiency is debated and its use discouraged due to toxicity; decanoic acid (HC10) a long-chain fatty acid that has been proposed as treatment for heritage objects; benzotriazole-5-carboxylic acid (5CBT), a compound with mixed azole-carboxylic functions.The reactivity of the inhibitors with synthetic mineral phases representative of corrosion products as well as ancient corroded samples (100 years) before and after 6-months outdoor exposure have been investigated by combining observations at the nanoscale (TEM, FIB-tomography) to those obtained at the microscale (Raman, SEM-EDS) and global/bulk observations (colour, surface tension, XRD). Additional experiments in marked environment allowed to investigate changes in permeability (D₂O immersion) and the evolution of passive behavior (KBr immersion).Two reaction mechanisms have been observed and a relationship with the efficiency and durability of the inhibition is proposed. The molecules BTAH and 5CBT interaction with copper atoms occurs via the azole function and both molecules react according to an adsorption-precipitation mechanism forming an adsorbed amorphous complex (nanometric film) on the substrate mineral phase (cuprite and brochantite). The two treatments on the ancient corrosion layers differ for their depth of penetration, with Cu-BTAH complex formation being detected until the cuprite inner layer, while 5CBT complexation is observed only in the outer part of the brochantite. This has an impact on the water permeability and passivity, with the BTAH treatments showing the best results, and suggests a complex formation with the outer cuprite layer in this last treatment. The carboxylic function in HC10 leads to the precipitation of copper decanoate by a dissolution-precipitation mechanism. Crystals of decanoate are formed on the outer surface of brochantite: this confers near super-hydrophobicity to the sample after treatment. However, the lack of bond between the precipitate and the surface determines the loss of the surface-deposited hydrophobic layer after 6 months of outdoor exposure.In addition to these phenomenological results, a new methodology based on the KBr experiment for testing inhibitors for copper corroded artefacts is also proposed.

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    Doctoral thesis . 2021
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      Doctoral thesis . 2021
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    Authors: Travers, Alice; Venturi, Federica;

    International audience

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    Authors: GADAL, Sébastien;

    International audience; This research explores the contribution of the Delisle brothers –Joseph-Nicolas and Louis – to the geography, cartography, and the discovery of Eastern Siberia, the Bering passage, and the Pacific Arctic. Their contribution to the European geographic and cartographic sciences is inestimable; as well as for the Russian Empire. They created the first general map of Russia, made the first analytic description of the Russian geography (biogeographic, physical, and human), especially in the Caucasus, Siberia, and in the Far-Eastern Arctic territories including Alaska. Joseph-Nicolas Delisle created the first department of geography in Saint-Petersburg, an astronomic observatory, and supervised the researches of the next generation of famous French and Russian Academics in Astronomy and geography.

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    Authors: Ahmadi, Sina; Constant, Mathieu; Fort, Karën; Guillaume, Bruno; +1 Authors

    Nous présentons dans ce papier les travaux que nous avons réalisés pour convertir dans le modèle Ontolex-Lemon l'une des plus importantes ressources lexicographiques pour le français : le Trésor de la Langue Française. En effet, malgré l'utilisation généralisée de cette ressource, son format actuel, basé sur XML, ne respecte pas les standards les plus récents de la représentation des données lexicographiques, notamment ceux basés sur les données liées. Nos travaux mettent en lumière la nécessité d'établir des mécanismes permettant d'augmenter l'inter-opérabilité des ressources et des technologies pour créer et maintenir des ressources lexicographiques. In this paper, we report our efforts to convert one of the most comprehensive lexicographic resources of French, the Trésor de la Langue Française, into the Ontolex-Lemon model. Despite the widespread usage of this resource, the original XML format seems to impede its integration in language technology tools. In order to breathe new life into this resource, we examine the usage and the conversion to more interoperable formats, primarily those based on the linguistic linked data, to provide this resource to a broader range of applications and users. National audience

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    ZENODO
    Article . 2021
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    Conference object . 2021
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    Other literature type . 2021
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      Article . 2021
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      Conference object . 2021
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      Other literature type . 2021
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    Authors: Vidale, Massimo; Desset, Francois; Caldana, Irene;

    The modern looting of a Bronze Age grave located at the site of Mahtoutabad (near Konar Sandal South, Jiroft) has, for the first time, revealed a range of ceramic materials that accompanied the carved chlorite artefacts of the Halil Rud or Jiroft style. In this paper we present and examine an assemblage of recovered finds including a carved chlorite shard and their archaeological context followed by a discussion specifically related to the original funerarydeposit. Finally, by conducting a cross-comparative survey between the recovered objects and those from other Early Bronze age sites of the region, we provide a possible, preliminary chronology for the looted grave of Mahtoutabad. International audience

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    Article . 2022
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  • Authors: Gutehrlé, Nicolas; Atanassova, Iana;

    This dataset is intended for training and testing Logical Layout Analysis and recognition system on French historical documents published between 1900 and 1950. The original data is part of the "Fond régional: Franche-Comté", which is curated by Gallica, the digital portal of the Bibliothèque Nationale de France (BnF). It is available on Zenodo at the following adress: https://zenodo.org/record/5752440#.YboX6lPjJhE; This dataset is intended for training and testing Logical Layout Analysis and recognition system on French historical documents published between 1900 and 1950. The original data is part of the "Fond régional: Franche-Comté", which is curated by Gallica, the digital portal of the Bibliothèque Nationale de France (BnF). It is available on Zenodo at the following adress: https://zenodo.org/record/5752440#.YboX6lPjJhE

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  • Authors: Gorlla, Cyril;

    Within the context of online shopping, it is often imperative to respond to customer queries promptly. In this paper, we explore and evaluate various methods of responding to binary customer questions with machine learning algorithms. Specifically, we implement models based on logistic probabilities as well as collaborative filtering in order to predict the response to binary questions on Amazon. We find that probabilistic models fare the best on our validation set (which includes unseen data), with the logistic model trained with vector embeddings achieving 67.6% accuracy.

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  • Authors: Quashie, Hélène;

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  • Authors: Torres Aguilar, Sergio; Stutzmann, Dominique;

    International audience; This paper presents the process of annotating and modelling a corpus to automatically detect named entities in medieval charters in French. It introduces a new annotated corpus and a new system which outperforms state-of-the art libraries. Charters are legal documents and among the most important historical sources for medieval studies as they reflect economic and social dynamics as well as the evolution of literacy and writing practices. Automatic detection of named entities greatly improves the access to these unstructured texts and facilitates historical research. The experiments described here are based on a corpus encompassing about 500k words (1200 charters) coming from three charter collections ofthe 13th and 14th centuries. We annotated the corpus and then trained two state-of-the art NLP libraries for Named Entity Recognition (Spacy and Flair) and a custom neural model (Bi-LSTM-CRF). The evaluation shows that all three models achieve a high performance rate on the test set and a high generalization capacity against two external corpora unseen during training. This paper describes the corpus and the annotation model, and discusses the issues related to the linguistic processing of medieval French and formulaic discourse, so as to interpret the results within a larger historical perspective.

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    Authors: Vorakitphan, Vorakit;

    La désinformation, dont la propagation s’est accentuée par le biais des médias sociaux, suscite aujourd’hui une réelle menace pour la société. Il existe différents moyens de véhiculer de la désinformation, par exemple par le biais de contenus délibérément manipulés ou fabriqués dans le but de créer des théories conspirationnistes, de rumeurs ou encore de positions et jugements erronés, tels que l’on peut en rencontrer dans des articles d'actualité, discours et débats politiques. L'une des nombreuses formes de désinformation rencontrée en ligne, et certainement l'une des plus dangereuses, est la propagande. Ce type de désinformation, que l’on retrouve notamment en politique, représente une stratégie de communication efficace mais souvent trompeuse utilisée pour promouvoir un certain point de vue auprès du public. La nécessité d'identifier, de classifier et de comprendre efficacement et automatiquement ce type de phénomène devient pressant. Dans cette thèse, j'aborde cette question et je propose une approche de classification fine des textes polarisés et de propagande issus d’articles de presse et de débats politiques. Selon le sujet abordé, le contexte, la source d'information, les antécédents et les préférences constituent un panel de facteurs pouvant influer sur les perceptions de l’auditoire et donc conduire à sa déviation ou polarisation en faveur d’un parti. À partir d’un cas d’utilisation provenant d’un scénario politique, nous proposons d’explorer les impacts d’une telle polarisation par le biais de méthodes issues de l’analyse de sentiment basée sur des aspects. L’objectif étant de vérifier dans quelle mesure ces méthodes peuvent permettre d’obtenir des informations sur les messages politiques postés sur les médias sociaux. Plus particulièrement, la thèse traite de la conception et de l'évaluation d'un certain nombre de techniques d'extraction des principales caractéristiques des textes de propagande dans le domaine du Traitement Automatique du Langage Naturel (TALN). L'analyse de sentiment, les techniques de persuasion, la simplicité des messages et l'argumentation y sont notamment proposées et étudiées en profondeur. Les résultats de cette thèse montrent que ces caractéristiques peuvent capturer des propriétés particulières permettant de caractériser la propagande dans les textes. D’autre part, ces caractéristiques sont employées dans le cadre de la conception et l'implémentation d'une architecture neuronale ayant pour vocation à détecter et classifier les techniques de propagande à grain fin. Le travail proposé dans cette thèse va au-delà de l'état de l'art des systèmes actuels de détection et de classification de la propagande à grain fin. En effet, plusieurs approches d'apprentissage automatique, allant de la régression logistique à des architectures neuronales récentes, ont été testées sur des jeux de données standard de détection de la propagande. En conséquence, un pipeline complet de détection et de classification de la propagande est présenté. La tâche de détection des extraits de textes de propagande a obtenu un score F1 de 0,71, et l'architecture basée sur les transformateurs a obtenu une moyenne de 0,67 pour la tâche de classification des techniques de propagande, surpassant ainsi les systèmes de pointe. Ce pipeline est démontré avec un outil de preuve de concept appelé PROTECT. Enfin, comme dernière contribution de cette thèse, j'ai participé à la création d'une nouvelle ressource linguistique annotée. Composée de textes issus des débats politiques des campagnes présidentielles américaines de 1960 à 2016, cette ressource est annotée avec 6 types de techniques de propagande qui se décomposent en 14 sous-catégories de propagande. L'ensemble de données que j'ai construit contient 1666 instances de propagande. In recent years, disinformation has become more viral, mainly due to its spread online on social media, leading to potential threatening consequences for the society. Heterogeneous forms of online disinformation are possible, i.e., deliberately manipulated or fabricated content with the intentional aim of creating conspiracy theories, rumours, or misbehaved stances and judgements, for instance, in news articles, and political discourse and debates. One of many instances of online disinformation, and certainly one of the most dangerous ones, is propaganda. This disinformation instance represents an effective but often misleading communication strategy which is employed to promote a certain viewpoint to the audience, for instance in the political context. The need to effectively and automatically identify, classify and understand such phenomenon is becoming a urgent need. In this thesis, I tackle this issue and I propose a fine-grained classification approach of polarized and propagandist text in news articles and political debates. More precisely, as the audience' perceptions are perceived differently depending on the context, the source of information, the audience background and preferences, a discussed topic can deviate or polarize the audience into a partisanship. This thesis firstly investigates such polarization given a use-case in a political scenario using Aspects-Based Sentiment Analysis to verify how extensively these methods can be employed to gain insights from the political posts on social media. The thesis discusses the design and evaluation of a number of techniques in extracting the main features of propagandist text in the area of Natural Language Processing (NLP) where sentiment analysis, persuasion techniques, message simplicity, and ultimately argumentation are proposed and thoroughly investigated. The findings in this thesis show that such features can capture particular characteristics of propaganda in texts. Furthermore, these features are employed to tackle the NLP tasks of propaganda detection and classification through the design and implementation of a neural architecture to classify fine-grained propaganda techniques. The work in this thesis goes beyond the state-of-the-art of current systems for fine-grained propaganda detection and classification. Various Machine Learning approaches ranging from feature-based logistic regression to recent neural architectures have been experimented on standard benchmarks in propaganda detection. As a result, a full pipeline in propaganda detection and classification is presented where the task of detecting the propagandist text snippets obtained .71 F1-score, and the transformer-based architecture obtained an average of .67 F1-score for the task of propaganda technique classification, outperforming the state-of-the-art systems. This pipeline is demonstrated with a proof-of-concept tool called PROTECT. Finally, as a last contribution of this thesis, I carried out the creation of a new annotated linguistic resource. This resource is annotated with 6 types of propaganda techniques, which breaks down into 14 sub-categories of propaganda in the political debates of the US presidential campaigns from 1960 to 2016. The data set I built contains 1666 instances of propagandist text.

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    Authors: Ferrari, Erika;

    Le patrimoine métallique est un témoin culturel de notre passé et, pour cette raison, sa préservation et sa transmission aux générations futures sont importantes. Plusieurs stratégies sont utilisées pour la protection du patrimoine cuivreux exposée en extérieur, dont l’utilisation des inhibiteurs de corrosion organiques. Les inhibiteurs utilisés pour le patrimoine sont généralement empruntés au domaine de l’industrie. Cependant, l’état de surface du métal, couvert par des couches de produits de corrosion complexes, et le protocole d’application des inhibiteurs diffèrent considérablement de l’application industrielle.La présente étude porte spécifiquement sur les inhibiteurs de corrosion pour la conservation des artefacts exposés à base de cuivre par une approche physico-chimique innovante. L'approche prend en compte la complexité de la couche de corrosion étudiée : une plaque de cuivre naturellement corrodée, représentative de la corrosion extérieure à long terme a été choisie. Pour l'étude, trois molécules organiques, caractérisées par des fonctions chimiques différentes ont été sélectionnées comme inhibiteurs de test : le benzotriazole (BTAH), un composé azolé, employé en conservation, dont l'efficacité est débattue et l’utilisation déconseillée en raison de sa toxicité ; l'acide décanoïque (HC10) un acide gras à longue chaîne qui a été proposé comme traitement pour les objets patrimoniaux ; l'acide benzotriazole-5-carboxylique (5CBT), un composé à fonctions mixtes azole-carboxyliques. La réactivité des inhibiteurs avec des phases minérales synthétiques représentatives des produits de corrosion ainsi que des échantillons corrodés anciens (100 ans) avant et après 6 mois d'exposition extérieure ont été étudiées en combinant des observations à l'échelle nanométrique (MET, FIB-tomographie) à celles obtenues à l'échelle microscopique (Raman, MEB-EDS) et des observations globales/globales (couleur, tension de surface, XRD). Des expériences complémentaires en milieux marqués ont permis d'étudier les évolutions de perméabilité (immersion en D₂O) et de comportement passif (immersion KBr). Deux mécanismes réactionnels ont été observés et une relation avec l'efficacité et la durabilité de l'inhibition est proposée. Les molécules caractérisées par la fonction azole (BTAH et 5CBT) réagissent selon un mécanisme d'adsorption-précipitation formant un complexe amorphe adsorbé (film nanométrique) sur la phase minérale substrat (cuprite et brochantite). Les deux traitements sur les couches anciennes de corrosion diffèrent par leur profondeur de pénétration, la formation du complexe BTAH étant détectée jusqu'à la couche interne de cuprite, tandis que la complexation 5CBT n'est observée que dans la partie externe de la brochantite. Ceci a un impact sur la perméabilité de l'eau et la passivité pour les traitements au BTAH qui montrent les meilleurs résultats, et suggère une formation de complexe Cu-BTA sur la partie externe de la couche de cuprite dans ce dernier traitement. La fonction carboxylique dans HC10 conduit à la précipitation du décanoate de cuivre par un mécanisme de dissolution-précipitation. Des cristaux de décanoate se forment sur la surface externe de brochantite : cela confère une quasi-superhydrophobie à l'échantillon après traitement. Cependant, le manque de liaison chimique forte entre le précipité et la surface induit la perte de la couche hydrophobe déposée en surface après 6 mois d'exposition à l'extérieur.En plus de ces résultats phénoménologiques, une nouvelle méthodologie basée sur l'expérience KBr pour tester les inhibiteurs des artefacts corrodés par le cuivre est également proposée. Metallic heritage artefacts represent cultural traces of our past, and for this reason, their preservation and transmission to future generations is important. To protect copper-based artworks exposed outdoors, several conservation strategies are followed, including the use of organic corrosion inhibitors. Inhibitors are usually borrowed from the industrial field. However, the surface state of the metal with the presence of complex corrosion layers, and the protocol of inhibitors' application differ considerably from the industrial ones.The present study specifically addresses corrosion inhibitors for conservation of copper-based exposed artifacts by an innovative physico-chemical approach. The approach takes into account the complexity of the corrosion layer under investigation: a naturally corroded copper plate, representative for outdoor long-term corrosion have been chosen. For the study, three organic molecules, characterized by different chemical functions have been selected as test inhibitors: benzotriazole (BTAH), an azole compound, employed in conservation, which efficiency is debated and its use discouraged due to toxicity; decanoic acid (HC10) a long-chain fatty acid that has been proposed as treatment for heritage objects; benzotriazole-5-carboxylic acid (5CBT), a compound with mixed azole-carboxylic functions.The reactivity of the inhibitors with synthetic mineral phases representative of corrosion products as well as ancient corroded samples (100 years) before and after 6-months outdoor exposure have been investigated by combining observations at the nanoscale (TEM, FIB-tomography) to those obtained at the microscale (Raman, SEM-EDS) and global/bulk observations (colour, surface tension, XRD). Additional experiments in marked environment allowed to investigate changes in permeability (D₂O immersion) and the evolution of passive behavior (KBr immersion).Two reaction mechanisms have been observed and a relationship with the efficiency and durability of the inhibition is proposed. The molecules BTAH and 5CBT interaction with copper atoms occurs via the azole function and both molecules react according to an adsorption-precipitation mechanism forming an adsorbed amorphous complex (nanometric film) on the substrate mineral phase (cuprite and brochantite). The two treatments on the ancient corrosion layers differ for their depth of penetration, with Cu-BTAH complex formation being detected until the cuprite inner layer, while 5CBT complexation is observed only in the outer part of the brochantite. This has an impact on the water permeability and passivity, with the BTAH treatments showing the best results, and suggests a complex formation with the outer cuprite layer in this last treatment. The carboxylic function in HC10 leads to the precipitation of copper decanoate by a dissolution-precipitation mechanism. Crystals of decanoate are formed on the outer surface of brochantite: this confers near super-hydrophobicity to the sample after treatment. However, the lack of bond between the precipitate and the surface determines the loss of the surface-deposited hydrophobic layer after 6 months of outdoor exposure.In addition to these phenomenological results, a new methodology based on the KBr experiment for testing inhibitors for copper corroded artefacts is also proposed.

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    Authors: Travers, Alice; Venturi, Federica;

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    Authors: GADAL, Sébastien;

    International audience; This research explores the contribution of the Delisle brothers –Joseph-Nicolas and Louis – to the geography, cartography, and the discovery of Eastern Siberia, the Bering passage, and the Pacific Arctic. Their contribution to the European geographic and cartographic sciences is inestimable; as well as for the Russian Empire. They created the first general map of Russia, made the first analytic description of the Russian geography (biogeographic, physical, and human), especially in the Caucasus, Siberia, and in the Far-Eastern Arctic territories including Alaska. Joseph-Nicolas Delisle created the first department of geography in Saint-Petersburg, an astronomic observatory, and supervised the researches of the next generation of famous French and Russian Academics in Astronomy and geography.

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    Authors: Ahmadi, Sina; Constant, Mathieu; Fort, Karën; Guillaume, Bruno; +1 Authors

    Nous présentons dans ce papier les travaux que nous avons réalisés pour convertir dans le modèle Ontolex-Lemon l'une des plus importantes ressources lexicographiques pour le français : le Trésor de la Langue Française. En effet, malgré l'utilisation généralisée de cette ressource, son format actuel, basé sur XML, ne respecte pas les standards les plus récents de la représentation des données lexicographiques, notamment ceux basés sur les données liées. Nos travaux mettent en lumière la nécessité d'établir des mécanismes permettant d'augmenter l'inter-opérabilité des ressources et des technologies pour créer et maintenir des ressources lexicographiques. In this paper, we report our efforts to convert one of the most comprehensive lexicographic resources of French, the Trésor de la Langue Française, into the Ontolex-Lemon model. Despite the widespread usage of this resource, the original XML format seems to impede its integration in language technology tools. In order to breathe new life into this resource, we examine the usage and the conversion to more interoperable formats, primarily those based on the linguistic linked data, to provide this resource to a broader range of applications and users. National audience

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    Authors: Vidale, Massimo; Desset, Francois; Caldana, Irene;

    The modern looting of a Bronze Age grave located at the site of Mahtoutabad (near Konar Sandal South, Jiroft) has, for the first time, revealed a range of ceramic materials that accompanied the carved chlorite artefacts of the Halil Rud or Jiroft style. In this paper we present and examine an assemblage of recovered finds including a carved chlorite shard and their archaeological context followed by a discussion specifically related to the original funerarydeposit. Finally, by conducting a cross-comparative survey between the recovered objects and those from other Early Bronze age sites of the region, we provide a possible, preliminary chronology for the looted grave of Mahtoutabad. International audience

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  • Authors: Gutehrlé, Nicolas; Atanassova, Iana;

    This dataset is intended for training and testing Logical Layout Analysis and recognition system on French historical documents published between 1900 and 1950. The original data is part of the "Fond régional: Franche-Comté", which is curated by Gallica, the digital portal of the Bibliothèque Nationale de France (BnF). It is available on Zenodo at the following adress: https://zenodo.org/record/5752440#.YboX6lPjJhE; This dataset is intended for training and testing Logical Layout Analysis and recognition system on French historical documents published between 1900 and 1950. The original data is part of the "Fond régional: Franche-Comté", which is curated by Gallica, the digital portal of the Bibliothèque Nationale de France (BnF). It is available on Zenodo at the following adress: https://zenodo.org/record/5752440#.YboX6lPjJhE

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  • Authors: Gorlla, Cyril;

    Within the context of online shopping, it is often imperative to respond to customer queries promptly. In this paper, we explore and evaluate various methods of responding to binary customer questions with machine learning algorithms. Specifically, we implement models based on logistic probabilities as well as collaborative filtering in order to predict the response to binary questions on Amazon. We find that probabilistic models fare the best on our validation set (which includes unseen data), with the logistic model trained with vector embeddings achieving 67.6% accuracy.

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  • Authors: Quashie, Hélène;

    International audience

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