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Register a new userMEAN: Multi-head Entity Aware Attention Networkfor Political Perspective Detection in News Media
يعني: الشبكة متعددة الرأس كيان إيلاء شبكة الاهتمام للكشف عن المنظور السياسي في وسائل الإعلام
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الطريقة التي يتم إنشاؤها ونشرها قد تغيرت بشكل كبير خلال العقد الماضي.إن تحديد المنظور السياسي يشكل طريقة مناقشة الأحداث المناقشة في وسائل الإعلام أكثر أهمية بسبب الزيادة الحادة في عدد منافذ الأخبار والمقالات.الأساليب السابقة عادة ما تستفيد فقط المعلومات اللغوية.ومع ذلك، فإن المقالات الإخبارية تحاول الحفاظ على المصداقية ويبدو أنها محايدة.لذلك، يتم تقديم التحيز بطرق خفية، عادة من خلال التركيز على جوانب مختلفة من القصة.في هذه الورقة، نقترح إطارا جديدا يعتبر الكيانات المذكريات في المقالات الإخبارية والمعرفة الخارجية بها، مما أسفر عن التحيز فيما يتعلق بهذه الكيانات.نستكشف طرق مختلفة لحقن معلومات الكيان في نموذج النص.تظهر التجارب أن إطار عملنا المقترح يحقق تحسينات كبيرة على النماذج النصية القياسية، وهو قادر على تحديد الفرق في روايات الأخبار مع وجهات نظر مختلفة.
The way information is generated and disseminated has changed dramatically over the last decade. Identifying the political perspective shaping the way events are discussed in the media becomes more important due to the sharp increase in the number of news outlets and articles. Previous approaches usually only leverage linguistic information. However, news articles attempt to maintain credibility and seem impartial. Therefore, bias is introduced in subtle ways, usually by emphasizing different aspects of the story. In this paper, we propose a novel framework that considers entities mentioned in news articles and external knowledge about them, capturing the bias with respect to those entities. We explore different ways to inject entity information into the text model. Experiments show that our proposed framework achieves significant improvements over the standard text models, and is capable of identifying the difference in news narratives with different perspectives.
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