Analyzing Emotional Trends from X platform using SenticNet: A Comparative Analysis with Cryptocurrency Price

التفاصيل البيبلوغرافية
العنوان: Analyzing Emotional Trends from X platform using SenticNet: A Comparative Analysis with Cryptocurrency Price
المؤلفون: Tash, Moein Shahiki, Ahani, Zahra, Kolesnikova, Olga, Sidorov, Grigori
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computation and Language, Computer Science - Machine Learning
الوصف: This study delves into the relationship between emotional trends from X platform data and the market dynamics of well-known cryptocurrencies Cardano, Binance, Fantom, Matic, and Ripple over the period from October 2022 to March 2023. Leveraging SenticNet, we identified emotions like Fear and Anxiety, Rage and Anger, Grief and Sadness, Delight and Pleasantness, Enthusiasm and Eagerness, and Delight and Joy. Following data extraction, we segmented each month into bi-weekly intervals, replicating this process for price data obtained from Finance-Yahoo. Consequently, a comparative analysis was conducted, establishing connections between emotional trends observed across bi-weekly intervals and cryptocurrency prices, uncovering significant correlations between emotional sentiments and coin valuations.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2405.03084
رقم الأكسشن: edsarx.2405.03084
قاعدة البيانات: arXiv