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Psychiatry on Twitter: Content Analysis of the Use of Psychiatric Terms in French
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In: ISSN: 2561-326X ; JMIR Formative Research ; https://hal.archives-ouvertes.fr/hal-03614832 ; JMIR Formative Research, JMIR Publications 2022, 6 (2), pp.e18539. ⟨10.2196/18539⟩ ; https://formative.jmir.org/2022/2/e18539 (2022)
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US-amerikanische Jiddische und Pennsylvania-Deutsche Medien zwischen lokaler Verankerung und Transnationalisierung
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In: ISSN: 0014-2115 ; EISSN: 2426-5543 ; Etudes Germaniques ; https://halshs.archives-ouvertes.fr/halshs-03559078 ; Etudes Germaniques, Klincksieck, 2022, Les études germaniques et le transnational : enjeux d’un questionnement scientifique et épistémologique, 76 (3), pp.379-398 (2022)
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| 3 |
« “Twitta” “Intellectuelle” “Influenceuse” ? Être enseignante-chercheuse sur twitter »
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In: ISSN: 1763-0061 ; EISSN: 1963-1812 ; Tracés : Revue de Sciences Humaines ; https://hal.archives-ouvertes.fr/hal-03592945 ; Tracés : Revue de Sciences Humaines, ENS Éditions, A paraître (2022)
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| 4 |
Renouvellement paradigmatique dans l’analyse des discours numériques : le cas de la communication politique sur les RSN
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In: ISSN: 2116-1747 ; Etudes de stylistique anglaise ; https://hal-amu.archives-ouvertes.fr/hal-03584927 ; Etudes de stylistique anglaise, Société de stylistique anglaise, Lyon, 2022, Renaissance(s)/Rebirth(s), ⟨10.4000/esa.4816⟩ ; https://journals.openedition.org/esa/4816 (2022)
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| 5 |
Chapter 11. Consumer opinion about smoked bacon using Twitter and textual analysis: The challenge continues
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In: Sensory Analysis for the Development of Meat Products ; https://hal-agrosup-dijon.archives-ouvertes.fr/hal-03575175 ; Sensory Analysis for the Development of Meat Products, Elsevier, pp.181-196, 2022, 9780128228326. ⟨10.1016/B978-0-12-822832-6.00013-8⟩ (2022)
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| 6 |
Förderung des Bildungsspracherwerbs bei heterogenen sprachlichen Voraussetzungen im Unterricht mit digitalen Medien ...
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| 7 |
#Bittersweet: Positive, negative, and mixed emotions in twitter posts ...
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| 8 |
Zum Ungleichgewicht digital vermittelten Sachunterrichts und sprachlich-kommunikativer Anforderungen ...
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| 10 |
Sprachliche Individualisierung mittels digitaler Medien
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In: Haider, Michael [Hrsg.]; Schmeinck, Daniela [Hrsg.]: Digitalisierung in der Grundschule. Grundlagen, Gelingensbedingungen und didaktische Konzeptionen am Beispiel des Fachs Sachunterricht. Bad Heilbrunn : Verlag Julius Klinkhardt 2022, S. 140-153 (2022)
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| 11 |
Förderung des Bildungsspracherwerbs bei heterogenen sprachlichen Voraussetzungen im Unterricht mit digitalen Medien
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In: Haider, Michael [Hrsg.]; Schmeinck, Daniela [Hrsg.]: Digitalisierung in der Grundschule. Grundlagen, Gelingensbedingungen und didaktische Konzeptionen am Beispiel des Fachs Sachunterricht. Bad Heilbrunn : Verlag Julius Klinkhardt 2022, S. 124-139 (2022)
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| 12 |
Zum Ungleichgewicht digital vermittelten Sachunterrichts und sprachlich-kommunikativer Anforderungen
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In: Sachunterricht in der Informationsgesellschaft. Bad Heilbrunn : Verlag Julius Klinkhardt 2022, S. 114-121. - (Probleme und Perspektiven des Sachunterrichts; 32) (2022)
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| 13 |
A Multilingual Dataset of COVID-19 Vaccination Attitudes on Twitter ...
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| 14 |
A Multilingual Dataset of COVID-19 Vaccination Attitudes on Twitter ...
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| 17 |
MULDASA: Multifactor Lexical Sentiment Analysis of Social-Media Content in Nonstandard Arabic Social Media
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In: Applied Sciences; Volume 12; Issue 8; Pages: 3806 (2022)
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Abstract:
The semantically complicated Arabic natural vocabulary, and the shortage of available techniques and skills to capture Arabic emotions from text hinder Arabic sentiment analysis (ASA). Evaluating Arabic idioms that do not follow a conventional linguistic framework, such as contemporary standard Arabic (MSA), complicates an incredibly difficult procedure. Here, we define a novel lexical sentiment analysis approach for studying Arabic language tweets (TTs) from specialized digital media platforms. Many elements comprising emoji, intensifiers, negations, and other nonstandard expressions such as supplications, proverbs, and interjections are incorporated into the MULDASA algorithm to enhance the precision of opinion classifications. Root words in multidialectal sentiment LX are associated with emotions found in the content under study via a simple stemming procedure. Furthermore, a feature–sentiment correlation procedure is incorporated into the proposed technique to exclude viewpoints expressed that seem to be irrelevant to the area of concern. As part of our research into Saudi Arabian employability, we compiled a large sample of TTs in 6 different Arabic dialects. This research shows that this sentiment categorization method is useful, and that using all of the characteristics listed earlier improves the ability to accurately classify people’s feelings. The classification accuracy of the proposed algorithm improved from 83.84% to 89.80%. Our approach also outperformed two existing research projects that employed a lexical approach for the sentiment analysis of Saudi dialects.
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Keyword:
Arabic NLP; Arabic social media; lexical; Saudi dialects; sentiment analysis; Twitter
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URL: https://doi.org/10.3390/app12083806
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| 18 |
Extracting Disaster-Related Location Information through Social Media to Assist Remote Sensing for Disaster Analysis: The Case of the Flood Disaster in the Yangtze River Basin in China in 2020
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In: Remote Sensing; Volume 14; Issue 5; Pages: 1199 (2022)
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| 19 |
Analysis of the Full-Size Russian Corpus of Internet Drug Reviews with Complex NER Labeling Using Deep Learning Neural Networks and Language Models
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In: Applied Sciences; Volume 12; Issue 1; Pages: 491 (2022)
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| 20 |
Social Media and the Pandemic: Consumption Habits of the Spanish Population before and during the COVID-19 Lockdown
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In: Sustainability; Volume 14; Issue 9; Pages: 5490 (2022)
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