SIFting تغريدات فرنسية للتحقيق في تأثير CovID-19 في إثارة القلق الشديد.يمكن الاستفادة من وسائل التواصل الاجتماعي لفهم المشاعر والمشاعر العامة في الوقت الفعلي، وتستهدف رسائل الصحة العامة المستندة إلى اهتمامات المستخدم والعواطف.في هذه الورقة، نحقق في تأثير الوباء CovID-19 في إثارة القلق الشديد، والاعتماد على الرسائل المتبادلة على Twitter.وبشكل أكثر تحديدا، نقدم: ط) إجراء تحليلا كميا ونوعيا لجور تغريدات باللغة الفرنسية ذات صلة بنظام Coronavirus، و II) نهج خط أنابيب (آلية ترشيح تليها أساليب الشبكة العصبية) مرضية للرسائل التي تعبر عن القلق الشديد على وسائل التواصل الاجتماعيبالنظر إلى الدور الذي تلعبه العواطف.
Sifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety. Social media can be leveraged to understand public sentiment and feelings in real-time, and target public health messages based on user interests and emotions. In this paper, we investigate the impact of the COVID-19 pandemic in triggering intense anxiety, relying on messages exchanged on Twitter. More specifically, we provide : i) a quantitative and qualitative analysis of a corpus of tweets in French related to coronavirus, and ii) a pipeline approach (a filtering mechanism followed by Neural Network methods) to satisfactory classify messages expressing intense anxiety on social media, considering the role played by emotions.
References used
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