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Register a new userClassification of Censored Tweets in Chinese Language using XLNet
تصنيف تغريدات الرقابة باللغة الصينية باستخدام XLNet
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في نمو العالم اليوم والتكنولوجيا المتقدمة، تلعب شبكات وسائل التواصل الاجتماعي دورا مهما في التأثير على الأرواح البشرية.الرقابة هي الإطاحة عن الكلام أو ناقل الحركة العام أو التفاصيل الأخرى التي تلعب دورا كبيرا في وسائل التواصل الاجتماعي.قد يتم اعتبار المحتوى ضارا أو حساسا أو غير مريح.السلطات مثل المعاهد والحكومات وغيرها من المنظمات تصرف الرقابة.نفذت هذه الورقة نموذجا يساعد على تصنيف التغريدات الرقابة والكشف عنها كتصنيف ثنائي.تصف الورقة تقديمها إلى مهمة مشتركة للرقابة في ورشة عمل NLP4IF 2021.استخدمنا العديد من النماذج المدربة المستندة إلى المحولات، وتخرج XLNet دقة أفضل بين الجميع.نحن نضقل النموذج للحصول على أداء أفضل وحققت دقة معقولة، وتحسب مقاييس الأداء الأخرى.
In the growth of today's world and advanced technology, social media networks play a significant role in impacting human lives. Censorship is the overthrowing of speech, public transmission, or other details that play a vast role in social media. The content may be considered harmful, sensitive, or inconvenient. Authorities like institutes, governments, and other organizations conduct Censorship. This paper has implemented a model that helps classify censored and uncensored tweets as a binary classification. The paper describes submission to the Censorship shared task of the NLP4IF 2021 workshop. We used various transformer-based pre-trained models, and XLNet outputs a better accuracy among all. We fine-tuned the model for better performance and achieved a reasonable accuracy, and calculated other performance metrics.
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