Analyzing Emotional Trends from X platform using SenticNet: A Comparative Analysis with Cryptocurrency Price
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866914785360084992 |
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| author | Tash, Moein Shahiki Ahani, Zahra Kolesnikova, Olga Sidorov, Grigori |
| author_facet | Tash, Moein Shahiki Ahani, Zahra Kolesnikova, Olga Sidorov, Grigori |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_03084 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Analyzing Emotional Trends from X platform using SenticNet: A Comparative Analysis with Cryptocurrency Price Tash, Moein Shahiki Ahani, Zahra Kolesnikova, Olga Sidorov, Grigori Computation and Language Machine Learning 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. |
| title | Analyzing Emotional Trends from X platform using SenticNet: A Comparative Analysis with Cryptocurrency Price |
| topic | Computation and Language Machine Learning |
| url | https://arxiv.org/abs/2405.03084 |