BitMood

BitMood: AI Analysis of Bitcoin Trends via Facebook Emotions

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Suggested citation

Pele, Daniel, Bag, Raul, and Gaman, Stefan (2024). BitMood. Q2 ecosystem. Available at https://quantinar.com/course/715/bitmoo or http://dx.doi.org/10.24818/IDA-CL/2024.2.

@misc{pele2024, author = {Pele, Daniel, Bag, Raul, and Gaman, Stefan}, title = {BitMood}, year = {2024}, howpublished = {Q2 ecosystem}, doi = {http://dx.doi.org/10.24818/IDA-CL/2024.2.}, url = {https://quantinar.com/course/715/bitmoo} }
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Courselet Content

2 components

	BitMood (video)	16 min
	BitMood (pdf)	10.05 M

Requirements

Statistics of Financial Market, Sentiment Analysis

General Overview

Description

The study has unveiled significant correlations between the sentiments expressed on Facebook and the fluctuations in Bitcoin trends. They not only reinforce the notion that public sentiment can be a powerful predictor of market trends but also open new avenues for understanding the intricate relationship between digital assets and online emotional expressions.