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1	Language transfer and positional bias in English stress
	Garcia, Guilherme Duarte. - 2020
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2	Language transfer and positional bias in English stress
	Garcia, Guilherme Duarte. - 2020
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3	Evaluating and Improving Child-Directed Automatic Speech Recognition
	Booth, Eric; Carns, Jake; Kennington, Casey...
	In: Computer Science Faculty Publications and Presentations (2020)
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4	Variation Impoverishment resulting from Machine Translations: Empirical Evidence from Spanish Counterfactual Predicates
	Repiso, Isabel
	In: ISSN: 2374-8850 ; International Journal of Language & Linguistics ; https://halshs.archives-ouvertes.fr/halshs-03330904 ; International Journal of Language & Linguistics, Center for Promoting Ideas, 2020, 7 (2), pp.21-28. ⟨10.30845/ijll.v7n2p3⟩ (2020)
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5	Variation Impoverishment resulting from Machine Translations: Empirical Evidence from Spanish Counterfactual Predicates
	Repiso, Isabel
	In: ISSN: 2374-8850 ; International Journal of Language & Linguistics ; https://halshs.archives-ouvertes.fr/halshs-03330904 ; International Journal of Language & Linguistics, Center for Promoting Ideas, 2020, 7, ⟨10.30845/ijll.v7n2p3⟩ (2020)
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6	Do spatial relational labels facilitate three-year-old children’s 2D to 3D transfer of relational information in a spatial mapping task?
	Tompkins, David Nicholas. - 2020
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7	Arctic snowpack characterization, climate monitoring and microwaves remote sensing ; Caractérisation du manteau neigeux arctique, suivi climatique et télédétection micro-onde
	Vargel, Céline. - : HAL CCSD, 2020
	In: https://tel.archives-ouvertes.fr/tel-03185802 ; Linguistique. Université Grenoble Alpes [2020-.]; Université de Sherbrooke (Québec, Canada), 2020. Français. ⟨NNT : 2020GRALU029⟩ (2020)
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8	Motivations of Low-Income Engineering Transfer Students Influencing Choice and Pursuit of Baccalaureate Degree Attainment
	Salgado, Leo. - : eScholarship, University of California, 2020
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9	Bootstrap methods for multi-task dependency parsing in low-resource conditions ; Méthodes d’amorçage pour l’analyse en dépendances de langues peu dotées
	Lim, Kyungtae. - : HAL CCSD, 2020
	In: https://tel.archives-ouvertes.fr/tel-03477961 ; Linguistics. Université Paris sciences et lettres, 2020. English. ⟨NNT : 2020UPSLE027⟩ (2020)
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10	Europe, l'autre cap, entre traductions et transferts
	Ehrhardt, Damien; Fleury, Hélène
	In: https://hal.archives-ouvertes.fr/hal-03124335 ; 2020 (2020)
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11	Clickbait detection using multimodel fusion and transfer learning ; Détection de clickbait utilisant fusion multimodale et apprentissage par transfert
	Praboda Chathurangani Rajapaksha, Rajapaksha Waththe Vidanelage. - : HAL CCSD, 2020
	In: https://tel.archives-ouvertes.fr/tel-03139880 ; Social and Information Networks [cs.SI]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAS025⟩ (2020)
	Abstract: Internet users are likely to be victims to clickbait assuming as legitimate news. The notoriety of clickbait can be partially attributed to misinformation as clickbait use an attractive headline that is deceptive, misleading or sensationalized. A major type of clickbait are in the form of spam and advertisements that are used to redirect users to web sites that sells products or services (often of dubious quality). Another common type of clickbait are designed to appear as news headlines and redirect readers to their online venues intending to make revenue from page views, but these news can be deceptive, sensationalized and misleading. News media often use clickbait to propagate news using a headline which lacks greater context to represent the article. Since news media exchange information by acting as both content providers and content consumers, misinformation that is deliberately created to mislead requires serious attention. Hence, an automated mechanism is required to explore likelihood of a news item being clickbait.Predicting how clickbaity a given news item is difficult as clickbait are very short messages and written in obscured way. The main feature that can identify clickbait is to explore the gap between what is promised in the social media post, news headline and what is delivered by the article linked from it. The recent enhancement to Natural Language Processing (NLP) can be adapted to distinguish linguistic patterns and syntaxes among social media post, news headline and news article.In my Thesis, I propose two innovative approaches to explore clickbait generated by news media in social media. Contributions of my Thesis are two-fold: 1) propose a multimodel fusion-based approach by incorporating deep learning and text mining techniques and 2) adapt Transfer Learning (TL) models to investigate the efficacy of transformers for predicting clickbait contents.In the first contribution, the fusion model is built on using three main features, namely similarity between post and headline, sentiment of the post and headline and topical similarity between news article and post. The fusion model uses three different algorithms to generate output for each feature mentioned above and fuse them at the output to generate the final classifier.In addition to implementing the fusion classifier, we conducted four extended experiments mainly focusing on news media in social media. The first experiment is on exploring content originality of a social media post by amalgamating the features extracted from author's writing style and online circadian rhythm. This originality detection approach is used to identify news dissemination patterns among news media community in Facebook and Twitter by observing news originators and news consumers. For this experiment, dataset is collected with our implemented crawlers from Facebook and Twitter streaming APIs. The next experiment is on exploring flaming events in the news media in Twitter by using an improved sentiment classification model. The final experiment is focused on detecting topics that are discussed in a meeting real-time aiming to generate a brief summary at the end.The second contribution is to adapt TL models for clickbait detection. We evaluate the performance of three TL models (BERT, XLNet and RoBERTa) and delivered a set of architectural changes to optimize these models.We believe that these models are the representatives of most of the other TL models in terms of their architectural properties (Autoregressive model vs Autoencoding model) and training datasets. The experiments are conducted by introducing advanced fine-tuning approaches to each model such as layer pruning, attention pruning, weight pruning, model expansion and generalization. To the best of authors' knowledge, there have been an insignificant number of attempts to use TL models on clickbait detection tasks and no any comparative analysis of multiple TL models focused on this task. ; Presque tous les internautes sont susceptibles d'être victimes de clickbait, supposant à tort qu’il s’agit d’informations légitimes. Un type important de clickbait se présente sous la forme de spam et de publicités qui sont utilisés pour rediriger les utilisateurs vers des sites web. Un autre type de "clickbait" est conçu pour faire la une des journaux et rediriger les lecteurs vers leurs sites en ligne, mais ces nouvelles sensationnelles peuvent être trompeuses. Il est difficile de prédire le degré de click-baity d'une nouvelle donnée car les clickbait sont des messages très courts et écrits de manière souvent obscure. La principale caractéristique qui permet d'identifier les clickbait est d'explorer l'écart entre ce qui est attendu dans un post, le titre de l'information et l’information réellement présente dans l'article qui y est lié. Dans cette thèse, on propose deux approches innovantes pour explorer le clickbait généré par les médias d'information dans les médias sociaux. Les contributions 1) de proposer une approche multimodèle basée sur la fusion en incorporant des techniques d'apprentissage profond et d'exploration de texte et 2) d’adapter les modèles d'apprentissage par transfert (TL) pour étudier l'efficacité des transformateurs permettant de prédire le contenu des clickbaits.
	Keyword: [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]; Analyse des sentiments; Apprentissage par transfert; Apprentissage profond; Clickbait; Deep learning; Médias d'information; Médias sociaux; News media; Sentiment analysis; Social media; Transfer learning
	URL: https://tel.archives-ouvertes.fr/tel-03139880 https://tel.archives-ouvertes.fr/tel-03139880/file/98914_PRABODA_CHATHURANGANI_RAJAPAKSHA_2020_ARCHIVAGE.pdf https://tel.archives-ouvertes.fr/tel-03139880/document
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12	Forschungsinstrumente im Kontext institutioneller (schrift-)sprachlicher Bildung ...
	null. - : Verlag Julius Klinkhardt, 2020
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13	Einleitung: Instrumente zur Erfassung institutioneller (schrift-)sprachlicher Bildung ...
	Mackowiak, Katja; Beckerle, Christine; Gentrup, Sarah. - : Verlag Julius Klinkhardt, 2020
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14	Transfer Learning of Grounded Language Models For Use In Robotic Systems ...
	Jenkins, Patrick. - : Maryland Shared Open Access Repository, 2020
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15	КОГНИТИВНЫЕ ОСНОВАНИЯ ГЛАГОЛЬНОЙ МЕТОНИМИИ В РЕПРЕЗЕНТАЦИИ РЕЧЕВЫХ ДЕЙСТВИЙ ... : COGNITIVE BASES OF VERBAL METONYMY IN THE REPRESENTATION OF SPEECH ACTS ...
	Чаплин, Е.В.; Сулейманова, О.А.. - : Государственное автономное образовательное учреждение высшего образования города Москвы «Московский городской педагогический университет», 2020
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16	Einleitung: Instrumente zur Erfassung institutioneller (schrift-)sprachlicher Bildung
	Mackowiak, Katja; Beckerle, Christine; Gentrup, Sarah...
	In: Mackowiak, Katja [Hrsg.]; Beckerle, Christine [Hrsg.]; Gentrup, Sarah [Hrsg.]; Titz, Cora [Hrsg.]: Forschungsinstrumente im Kontext institutioneller (schrift-)sprachlicher Bildung. Bad Heilbrunn : Verlag Julius Klinkhardt 2020, S. 7-12 (2020)
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17	Formen der (Re-)Präsentation fachlichen Wissens. Ansätze und Methoden für die Lehrerinnen- und Lehrerbildung in den Fachdidaktiken und den Bildungswissenschaften
	Interdisziplinäre Tagung "Formen der (Re-)Präsentation Fachlichen Wissens - Ansätze und Methoden für die Lehrerbildung in den Fachdidaktiken und den Bildungswissenschaften" (2018 : Kiel). - : Waxmann, 2020. : Münster, 2020. : New York, 2020. : pedocs-Dokumentenserver/DIPF, 2020
	In: Münster ; New York : Waxmann 2020, 262 S. (2020)
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18	Das Transferverständnis aus Sicht der Sozialarbeitsstudierenden
	Radeiski, Bettina
	In: Die Hochschule : Journal für Wissenschaft und Bildung 29 (2020) 2, S. 44-54 (2020)
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19	Forschungsinstrumente im Kontext institutioneller (schrift-)sprachlicher Bildung
	Gentrup, Sarah Hrsg.; Mackowiak, Katja Hrsg.; Beckerle, Christine Hrsg.. - : Verlag Julius Klinkhardt, 2020. : Bad Heilbrunn, 2020. : pedocs-Dokumentenserver/DIPF, 2020
	In: Bad Heilbrunn : Verlag Julius Klinkhardt 2020, 159 S. (2020)
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20	"Les fondements communs de nos démocraties modernes". Persönliche Eindrücke aus einem französisch-deutsch-ungarischen Erasmus+ Projekt
	Scholten, Alfons
	In: Quoi de neuf : nouvelle du bilingue (2020), S. 61-75 (2020)
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