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Predicting Bitcoin Prices Using Sentiment Analysis Results

Published: 09 July 2022 Publication History

Abstract

Sentiment Analysis is a technique to determine the tone of a statement using computer software. It is an appliance of a linguistic and computer science intersection that could make a great impact on the business field. Lately, Sentiment Analysis has been used on social media platforms such as Twitter or Facebook to observe the tone of a statement. Examining the tone of tweets using the computer could be time-efficient and precise. SA studies could also be linked to Bitcoin. In this paper, I am using SA results of tweets on a given day to predict changes in the Bitcoin price and its returns. First, I collected the data, which included 31 data points of average sentiment scores and the corresponding 31 Bitcoin prices on the same day. The average sentiment scores were evaluated by VADER from a scale of -1 to 1 (-1 being the statements with the most negative tone, and 1 with the most positive). Then, I used linear regressions to predict Bitcoin price and returns using sentiment scores on the previous day/days. Predicting returns based on sentiments could allow me to find the relationship between Twitter users and Bitcoin and help me better understand the potential challenges. In the end, the predicted price was positively correlated to the sentiment scores the day before. Interestingly, the predicted return was negatively correlated with the sentiment scores and showed less correlation with a M coefficient of -0.86125.

References

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Zhang, Lei, Shuai Wang, and Bing Liu."Deep Learning for Sentiment Analysis: A Survey." Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 8 4 (2018).
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Mohey El-Din Mohamed Hussein, Doaa. "A Survey on Sentiment Analysis Challenges." Journal of King Saud University-Engineering Sciences 30, no. 4 (October 2018): 330-38.
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Cambria, Erik, Dipankar Das, Sivaji Bandyopadhyay, and Antonio Feraco."A Practical Guide to Sentiment Analysis." Springer International Publishing, 2017.
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Pano, Toni, and Rasha Kashef. "A Complete VADER-Based Sentiment Analysis of Bitcoin (BTC) Tweets during the Era of COVID-19."Big Data and Cognitive Computing 4 (2020).

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  1. Predicting Bitcoin Prices Using Sentiment Analysis Results

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    ICEEG '22: Proceedings of the 6th International Conference on E-Commerce, E-Business and E-Government
    April 2022
    439 pages
    ISBN:9781450396523
    DOI:10.1145/3537693
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 09 July 2022

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    Author Tags

    1. Bitcoin
    2. Forecasting
    3. Quantitative Finance
    4. Sentiment Analysis
    5. Twitter

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