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Register a new userA Psychologically Informed Part-of-Speech Analysis of Depression in Social Media
تحليل جزء من الكلام غير المستنير نفسيا للاكتئاب في وسائل التواصل الاجتماعي
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في هذا العمل، نقدم تحليل جزء واسع النطاق لخطاب مستخدمي وسائل التواصل الاجتماعي مع الاكتئاب.كشفت الأبحاث في علم النفس أن المستخدمين الاكتئابين يميلون إلى أن يكونوا مركزة ذاتيا، أكثر انشغالا مع أنفسهم ويقومون بإعادة المزيد عن حياتهم وعواطفهم.يهدف عملنا إلى الاستفادة من مجموعات بيانات واسعة النطاق والأساليب الحسابية لاستكشاف خطابي كمي.نحن نستخدم مجموعة بيانات الاكتئاب المتاحة للجمهور من التنبؤ بالمخاطر المبكرة في ورشة عمل الإنترنت (ERISK) 2018 واستخراج ميزات جزء من الكلام والعديد من المؤشرات بناء عليها.تكشف نتائجنا عن فروق ذات دلالة إحصائية بين الأفراد الاكتئاب وغير الاكتئاب الذين يؤكدون النتائج من أدب علم النفس الحالي.يوفر عملنا نظرة ثاقبة فيما يتعلق بالطريقة التي يعبر فيها الأفراد الاكتئاب عن أنفسهم على منصات وسائل التواصل الاجتماعي، مما يتيح لنماذج حسابية على علم أفضل للمساعدة في مراقبة الأمراض العقلية ومنعها.
In this work, we provide an extensive part-of-speech analysis of the discourse of social media users with depression. Research in psychology revealed that depressed users tend to be self-focused, more preoccupied with themselves and ruminate more about their lives and emotions. Our work aims to make use of large-scale datasets and computational methods for a quantitative exploration of discourse. We use the publicly available depression dataset from the Early Risk Prediction on the Internet Workshop (eRisk) 2018 and extract part-of-speech features and several indices based on them. Our results reveal statistically significant differences between the depressed and non-depressed individuals confirming findings from the existing psychology literature. Our work provides insights regarding the way in which depressed individuals are expressing themselves on social media platforms, allowing for better-informed computational models to help monitor and prevent mental illnesses.
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