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Predicting the Success of Internet Social Welfare Crowdfunding Based on Text Information
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In: Applied Sciences; Volume 12; Issue 3; Pages: 1572 (2022)
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How We Failed in Context: A Text-Mining Approach to Understanding Hotel Service Failures
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In: Sustainability; Volume 14; Issue 5; Pages: 2675 (2022)
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Tracing the Legitimacy of Artificial Intelligence – A Media Analysis, 1980-2020
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Dynamics of prescriptivism and lexical borrowings in Contemporary French
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Abstract:
In France and Québec, language contact with English is often perceived as a source of negative influence on French. Terminological commissions working under the supervision of the Académie française and the Office québécois de la langue française are tasked to replace foreign words and expressions with French terminology that is mandatory in all government publications. However, the general public is merely encouraged to comply with these recommendations: the actual use of these top-down lexical innovations remains to be established. Using examples from newspaper and social media corpora, this study investigates how speakers comply with the use of prescribed French terminology, including emblematic lexical innovations such as courriel and mot-dièse, rather than their English equivalents. The research combines quantitative and qualitative methodologies applied on large corpora of formal and informal written texts from France and Québec. The first quantitative component comprises newspaper articles from 2000 to 2017 in order to examine whether purist recommendations are implemented in formal written language. Time is treated with a new dynamic approach: the probability of use of a prescribed term is estimated three years before and three years after official prescription. 54 target terms are selected from the lexical fields of computer science, entertainment industry and telecommunication. The second quantitative component consists of tweets published from January 2010 to December 2016, targeting 4 lexical items recurring with high frequency in the newspaper corpus. Statistical analyses were implemented on variables of gender (male or female users), social media influence score, and urban population size, complemented with mapping the diffusion of lexical innovations in France and Québec. The third, qualitative component explores reactions to prescription in tweets and newspapers, examined with sentiment analysis and close reading. The analyses reveal that prescription is primarily effective when it follows already attested usage, as demonstrated in the estimated probability of use in both the newspaper and the social media corpora. Conservative newspapers show higher proportions of recommended terminology, especially as compared to newspapers specializing in technology. Language users express more prescriptive attitudes in Québec than they do in France, which signals the perception of failed top-down intervention on French social media, but a successful one among Québécois users. These results corroborate previous scholarship on regional variation toward prescription, partly due to English being a prestigious foreign language in France as opposed to a native language in Québec where Francophone speakers showcase stronger linguistic purism against it. ; Limited ; Author requested closed access (OA after 2yrs) in Vireo ETD system
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Keyword:
Académie française; France; French; French Academy; language contact; lexical borrowing; loanwords; newspaper; prescriptivism; purism; Quebec; sentiment analysis; terminology; text mining; Twitter
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URL: http://hdl.handle.net/2142/108261
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Sentiment Analysis of Arabic Documents
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In: Natural Language Processing for Global and Local Business ; https://hal.archives-ouvertes.fr/hal-03124729 ; Fatih Pinarbasi; M. Nurdan Taskiran. Natural Language Processing for Global and Local Business, pp.307-331, 2021, 9781799842408. ⟨10.4018/978-1-7998-4240-8.ch013⟩ ; https://www.igi-global.com/ (2021)
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On Multi-domain Sentence Level Sentiment Analysis for Roman Urdu ...
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Developing Conversational Data and Detection of Conversational Humor in Telugu ...
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Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification ...
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Open Aspect Target Sentiment Classification with Natural Language Prompts ...
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SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis ...
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Connecting Attributions and QA Model Behavior on Realistic Counterfactuals ...
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Solving Aspect Category Sentiment Analysis as a Text Generation Task ...
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CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks ...
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Improving Multimodal fusion via Mutual Dependency Maximisation ...
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Improving Federated Learning for Aspect-based Sentiment Analysis via Topic Memories ...
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How much coffee was consumed during EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI ...
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