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Register a new userDoes Commonsense help in detecting Sarcasm?
هل مساعدة المنطقية في الكشف عن السخرية؟
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الكشف عن السخري مهم بالنسبة للعديد من مهام NLP مثل تحديد المعنويات في مراجعات المنتج وملاحظات المستخدم والمنتديات عبر الإنترنت.إنها مهمة صعبة تتطلب فهم عميق للغة والسياق والمعرفة العالمية.في هذه الورقة، نحقق ما إذا كانت دمج المعرفة المنطقية تساعد في الكشف عن السخرية.بالنسبة لهذا، فإننا ندمج معارف المنطقية في عملية التنبؤ باستخدام شبكة استئصال الرسم البياني مع تضيير نموذج اللغة المدرب مسبقا كمدخلات.تشير تجاربنا المزودة بثلاث مجموعات بيانات للكشف عن السخرية إلى أن النهج لا يتفوق على النموذج الأساسي.نحن نقوم بإجراء مجموعة شاملة من التجارب لتحليل المكان الذي يضيف فيه دعم المنطقي قيمة وأين يضر التصنيف.ينطبق تنفيذنا علنا على: https://github.com/brcsomnath/commonseense-sarasmasr.
Sarcasm detection is important for several NLP tasks such as sentiment identification in product reviews, user feedback, and online forums. It is a challenging task requiring a deep understanding of language, context, and world knowledge. In this paper, we investigate whether incorporating commonsense knowledge helps in sarcasm detection. For this, we incorporate commonsense knowledge into the prediction process using a graph convolution network with pre-trained language model embeddings as input. Our experiments with three sarcasm detection datasets indicate that the approach does not outperform the baseline model. We perform an exhaustive set of experiments to analyze where commonsense support adds value and where it hurts classification. Our implementation is publicly available at: https://github.com/brcsomnath/commonsense-sarcasm.
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This is a research proposal for doctoral research into sarcasm detection, and the real-time compilation of an English language corpus of sarcastic utterances. It details the previous research into similar topics, the potential research directions and the research aims.
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