使用 SenticNet 分析来自 X 平台的情感趋势:与加密货币价格的对比分析

IF 4.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Moein Shahiki Tash, Zahra Ahani, Mohim Tash, Olga Kolesnikova, Grigori Sidorov
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引用次数: 0

摘要

本研究探讨了 2022 年 10 月至 2023 年 3 月期间,从 X 平台数据中得出的情绪趋势与著名加密货币--Cardano、Binance、Fantom、Matic 和 Ripple--的市场动态之间的关系。利用 SenticNet,识别出了恐惧和焦虑、愤怒和生气、悲伤和难过、高兴和愉快、热情和渴望以及高兴和喜悦等关键情绪。分析了情绪数据和加密货币价格数据(每两周一次),以发现显著的相关性。研究结果表明,喜悦和愉快、高兴和喜悦等情绪与 Fantom 的价格具有最强的正相关性,而喜悦和愉快与 Cardano 和 Binance 的价格具有最强的负相关性。这项研究强调了特定情绪状态对加密货币价格的细微影响,为市场参与者提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Analyzing Emotional Trends from X Platform Using SenticNet: A Comparative Analysis with Cryptocurrency Price

Analyzing Emotional Trends from X Platform Using SenticNet: A Comparative Analysis with Cryptocurrency Price

This study investigates the relationship between emotional trends derived from X platform data and the market dynamics of prominent cryptocurrencies—Cardano, Binance, Fantom, Matic, and Ripple—during the period from October 2022 to March 2023. Utilizing SenticNet, key emotions such as fear and anxiety, rage and anger, grief and sadness, delight and pleasantness, enthusiasm and eagerness, and delight and joy were identified. The emotional data and cryptocurrency price data, sourced bi-weekly, were analyzed to uncover significant correlations. The findings reveal that emotions such as delight and pleasantness and delight and joy have the strongest positive correlations with Fantom’s price, while delight and pleasantness exhibit the strongest negative correlations with Cardano and Binance. The study highlights the nuanced impact of specific emotional states on cryptocurrency prices, offering valuable insights for market participants.

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来源期刊
Cognitive Computation
Cognitive Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-NEUROSCIENCES
CiteScore
9.30
自引率
3.70%
发文量
116
审稿时长
>12 weeks
期刊介绍: Cognitive Computation is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of natural and artificial cognitive systems. It provides a new platform for the dissemination of research, current practices and future trends in the emerging discipline of cognitive computation that bridges the gap between life sciences, social sciences, engineering, physical and mathematical sciences, and humanities.
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