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Η επίδραση των κοινωνικών μέσων δικτύωσης στον σχεδιασμό ενός ταξιδιού: Ταξιδιωτική πρόθεση και αντίληψη κινδύνου κατά τη διάρκεια της πανδημίας
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The Rhetoric of Psychopathology: An Interdisciplinary Approach to Understanding and Talking About Mental Health
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Influencer detection in social media ; Détection des influenceurs dans des médias sociaux
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In: https://tel.archives-ouvertes.fr/tel-03640442 ; Ordinateur et société [cs.CY]. Institut National des Langues et Civilisations Orientales- INALCO PARIS - LANGUES O', 2021. Français. ⟨NNT : 2021INAL0034⟩ (2021)
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Hate speech and offensive language detection using transfer learning approaches ; Détection du discours de haine et du langage offensant utilisant des approches de Transfer Learning
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In: https://tel.archives-ouvertes.fr/tel-03276023 ; Document and Text Processing. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAS007⟩ (2021)
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Influencer detection in social media ; Détection des influenceurs dans des médias sociaux
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In: https://tel.archives-ouvertes.fr/tel-03640442 ; Ordinateur et société [cs.CY]. Institut National des Langues et Civilisations Orientales- INALCO PARIS - LANGUES O', 2021. Français. ⟨NNT : 2021INAL0034⟩ (2021)
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Generating health evidence from social media ; Extração de informação de saúde através das redes sociais
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Studying depression through big data analytics on Twitter
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In: TDX (Tesis Doctorals en Xarxa) (2021)
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Abstract:
Mental disorders have become a major concern in public health, since they are one of the main causes of the overall disease burden worldwide. Depressive disorders are the most common mental illnesses, and they constitute the leading cause of disability worldwide. Language is one of the main tools on which mental health professionals base their understanding of human beings and their feelings, as it provides essential information for diagnosing and monitoring patients suffering from mental disorders. In parallel, social media platforms such as Twitter, allow us to observe the activity, thoughts and feelings of people’s daily lives, including those of patients suffering from mental disorders such as depression. Based on the characteristics and linguistic features of the tweets, it is possible to identify signs of depression among Twitter users. Moreover, the effect of antidepressant treatments can be linked to changes in the features of the tweets posted by depressive users. The analysis of this huge volume and diversity of data, the so-called “Big Data”, can provide relevant information about the course of mental disorders and the treatments these patients are receiving, which allows us to detect, monitor and predict depressive disorders. This thesis presents different studies carried out on Twitter data in the Spanish language, with the aim of detecting behavioral and linguistic patterns associated to depression, which can constitute the basis of new and complementary tools for the diagnose and follow-up of patients suffering from this disease
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Keyword:
616.89; Antidepressant drugs; Depression; Mental health; Selective serotonin uptake inhibitors; Social media; Text mining; Twitter
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URL: http://hdl.handle.net/10803/671365
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Civility in digital discourse : an experimental approach to the contagion of thoughtful and hurtful responses
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Espraiamento do conservadorismo no Brasil das mídias sociais ; Spread of conservatism in Brazil on social networks
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Paiva, Síria Maria Andrade. - : Universidade Federal do Rio Grande do Norte, 2021. : Brasil, 2021. : UFRN, 2021. : Serviço Social, 2021. : Departamento de Serviço Social, 2021
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Content Selection for Effective Counter-Argument Generation
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Clickbait detection using multimodel fusion and transfer learning ; Détection de clickbait utilisant fusion multimodale et apprentissage par transfert
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In: https://tel.archives-ouvertes.fr/tel-03139880 ; Social and Information Networks [cs.SI]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAS025⟩ (2020)
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An old tradition in a new space : a critical discourse analysis of YouTubers' metalinguistic commentary on Quebec French
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Towards Subjective Multimedia Summarization Framework for Sporting Event in the Context of Digital Twins
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Detection and analysis of drug non-adherence in social media ; Détection et analyse de la non-adhérence médicamenteuse dans les réseaux sociaux
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In: https://tel.archives-ouvertes.fr/tel-02478927 ; Linguistique. Université de Lille, 2019. Français. ⟨NNT : 2019LILUH026⟩ (2019)
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Neologia de empresa: o Facebook como observatório de novas tendências em neologia
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Language, queerly phrased: a sociolinguistic examination of nonbinary gender identity in French
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Computational linguistics using social media to understand immigrant sentiment in the United States
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Bain, James. - : University of Missouri--Columbia, 2019
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