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Register a new userTREMoLo-Tweets: A Multi-Label Corpus of French Tweets for Language Register Characterization
Tremolo-Tweets: مجموعة متعددة التسمية من التغريدات الفرنسية للحصول على توصيف تسجيل اللغة
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السجلات غير الرسمية والمحايدة واللغة الرسمية ملموسة للغاية في إنتاج خطاب.ومع ذلك، ما زالوا مدروسين بشكل سيئ في معالجة اللغة الطبيعية (NLP)، وخاصة خارج اللغة الإنجليزية، ولأنواع نصية جديدة مثل التغريدات.لتحفيز البحث، تقدم هذه الورقة كجن كبير قدره 228،505 تغريدات فرنسية (6M كلمات) مشروح في سجلات اللغة.يتم توفير التسميات من قبل مصنف كاممبرت متعدد الملصقات المدربة وتحقق من مجموعة فرعية مشروحة يدويا من Corpus، في حين يتم تحديد التغريدات لتجنب التحيزات غير المرغوب فيها.بناء على Corpus، يتم توفير تحليل أولي للسمات اللغوية من النحاذج البشرية أو الاستخراج التلقائي لوصف Corpus وتمهيد الطريق لمكاميات NLP المختلفة.تتوفر Corpus، دليل التوضيحية والتصنيف على http://tremolo.irisa.fr.
The casual, neutral, and formal language registers are highly perceptible in discourse productions. However, they are still poorly studied in Natural Language Processing (NLP), especially outside English, and for new textual types like tweets. To stimulate research, this paper introduces a large corpus of 228,505 French tweets (6M words) annotated in language registers. Labels are provided by a multi-label CamemBERT classifier trained and checked on a manually annotated subset of the corpus, while the tweets are selected to avoid undesired biases. Based on the corpus, an initial analysis of linguistic traits from either human annotators or automatic extractions is provided to describe the corpus and pave the way for various NLP tasks. The corpus, annotation guide and classifier are available on http://tremolo.irisa.fr.
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