research-article

Bitcoin Price Prediction Considering Sentiment Analysis on Twitter and Google News

Authors:

Ameni Youssfi Nouira,

Mariam Bouchakwa,

Yassine JamoussiAuthors Info & Claims

IDEAS '23: Proceedings of the 27th International Database Engineered Applications Symposium

Pages 71 - 78

https://doi.org/10.1145/3589462.3589494

Published: 26 May 2023 Publication History

Abstract

Cryptocurrencies are digital currencies that operate on the blockchain, which is the technology that offers security and decentralization. The principal characteristic of cryptocurrencies is that they are not generally issued by a central authority. Many factors can influence the volatility of prices. This paper enables to drive insights into the behavior of markets through the application of sentiment analysis of Tweets, Google news and machine learning techniques for the challenging task of cryptocurrency price prediction. Most of the studies have focused exclusively on the sentiment analysis of tweets. In this work, we propose the use of common machine learning tools and available Google News data for predicting the price of crypto. We present the results of the Long Short-Term Memory (LSTM) model using Tweets and Google News data.

References

[1]

Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system (2008)

[2]

Sovbetov Y. Factors influencing cryptocurrency prices: Evidence from bitcoin, ethereum, dash, litcoin, and monero. Journal of Economics and Financial Analysis 2018;2(2):1–27.

[3]

Shubhankar Mohapatra, Nauman Ahmed, Paulo Alencar :KryptoOracle: A Real-Time Cryptocurrency Price Prediction Platform Using Twitter Sentiments, 2019 IEEE International Conference on Big Data (Big Data)

[4]

Toni Pano and Rasha Kashef A Complete VADER-Based Sentiment Analysis of Bitcoin (BTC) Tweets during the Era of COVID-19. Big Data Cogn. Comput. 2020.

[5]

Y. Sovbetov, “Factors influencing cryptocurrency prices: Evidence from bitcoin, ethereum, dash, litcoin, and monero,” Journal of Economics and Financial Analysis, vol. 2, no. 2, pp. 1–27, 2018.

[6]

Mohil MaheshkumarPatel, SudeepTanwar, RajeshGupta, NeerajKumar :A Deep Learning-based Cryptocurrency Price Prediction Scheme for Financial Institutions, Journal of Information Security and Applications Volume 55, December 2020, 102583

[7]

Zheshi Chen ∗, Chunhong Li, Wenjun Sun, Bitcoin price prediction using machine learning: An approach to sample dimension engineering, Journal of Computational and Applied Mathematics 365 (2020) 112395.

Digital Library

[8]

Connor Lamon, Eric Nielsen, Eric Redondo, Cryptocurrency Price Prediction Using News and Social Media Sentiment, SMU Data Sci. Rev, 2017 - cs229.stanford.edu.

[9]

C. J. Hutto and E. Gilbert, “VADER: A parsimonious rule-based model for sentiment analysis of social media text,” in Proceedings of the Eighth International Conference on Weblogs and Social Media, ICWSM 2014, Ann Arbor, Michigan, USA, June 1-4, 2014, 2014.

[10]

Chahat Tandon, Sanjana Revankar, Hemant Palivela Dr., Ph.D, Head of AI and Machine Learning, Sidharth Singh Parihar : How can we predict the impact of the social media messages on the value of cryptocurrency? Insights from big data analytics, International Journal of Information Management Data Insights 1 (2021) 100035

[11]

Pratikkumar Prajapati, PREDICTIVE ANALYSIS OF BITCOIN PRICE CONSIDERING SOCIAL SENTIMENTS. arXiv preprint arXiv:2001.10343, 2020 - arxiv.org

[12]

Jacques Vella Critien1*, Albert Gatt2 and Joshua Ellul1 Bitcoin price change and trend prediction through twitter sentiment and data volume, Critien et al. Financial Innovation (2022) 8:45

[13]

Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural computation 9, 1735–80 (1997)

[14]

Wu, Y., Schuster, M., Chen, Z., Le, Q.V., Norouzi, M., Macherey, W., Krikun, M., Cao, Y., Gao, Q., Macherey, K., : Google's neural machine translation system: Bridging the gap between human and machine translation. arXiv preprint arXiv:1609.08144 (2016)

[15]

Zhang, P., Ouyang, W., Zhang, P., Xue, J., Zheng, N.: Sr-lstm: State refinement for lstm towards pedestrian trajectory prediction. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 12085–12094 (2019)

[16]

Kanjo, E., Younis, E.M., Ang, C.S.: Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection. Information Fusion 49, 46 – 56 (2019)

Digital Library

[17]

Ning Tang, Yanyan Shen, and Junjie Yao, Learning to Fuse Multiple Semantic Aspects from Rich Texts for Stock Price Prediction20th International Conference Hong Kong, China, November 26–30, 2019 Proceedings Web Information Systems Engineering – WISE 2019

[18]

https://pypi.org/project/GoogleNews/ Accessed: 2022-05-09

[19]

Newspaper Python library. https://newspaper.readthedocs.io. Accessed: 2022-05-09

[20]

Pandas Python library. https://pandas.pydata.org. Accessed: 2022-05-08.

[21]

https://www.binance.com/en/binance-api Accessed: 2022-05-08.

[22]

S. Saravanakumar and V. D. Kumar, "High throughput quaternary signed digital adder design for portable electronic applications," International Journal of Pure and Applied Mathematics, vol. 116, no. 11, 2017, pp. 61-69.

Cited By

Fu YZhou MZhang L(2024)DAM: A Universal Dual Attention Mechanism for Multimodal Timeseries Cryptocurrency Trend Forecasting2024 IEEE International Conference on Metaverse Computing, Networking, and Applications (MetaCom)10.1109/MetaCom62920.2024.00025(73-80)Online publication date: 12-Aug-2024
https://doi.org/10.1109/MetaCom62920.2024.00025

Index Terms

Bitcoin Price Prediction Considering Sentiment Analysis on Twitter and Google News
1. Computing methodologies
  1. Machine learning
    1. Machine learning algorithms

Recommendations

Bitcoin Price Prediction Through Opinion Mining
WWW '19: Companion Proceedings of The 2019 World Wide Web Conference

The Bitcoin protocol and its underlying cryptocurrency have started to shape the way we view digital currency, and opened up a large list of new and interesting challenges. Amongst them, we focus on the question of how is the price of digital currencies ...
Deep Learning and Sentiment Analysis-Based Cryptocurrency Price Prediction
Advances in Visual Informatics
Abstract
The rapid growth of Cryptocurrency dramatically influences the social and economic climate that has developed the trends for investors to seek opportunities for generating income from cryptocurrency investment trading. Cryptocurrency is volatile ...
Bitcoin Price Forecasting: Linear Discriminant Analysis with Sentiment Evaluation
ArabWIC 2021: The 7th Annual International Conference on Arab Women in Computing in Conjunction with the 2nd Forum of Women in Research

Cryptocurrencies such as bitcoin have garnered a lot of attention in recent months due to their meteoric rise. In this paper, we propose a new method for predicting the direction of bitcoin price using linear discriminant analysis (LDA) together with ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

IDEAS '23: Proceedings of the 27th International Database Engineered Applications Symposium

May 2023

222 pages

ISBN:9798400707445

DOI:10.1145/3589462

Editors:
Richard Chbeir
University Pau & Pays Adour, France
,
Mirjana Ivanovic
University of Novi Sad, Serbia
,
Yannis Manolopoulos
Open University of Cyprus, Cyprus
,
Peter Z. Revesz
University of Nebraska Lincoln, USA

Copyright © 2023 ACM.

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 the author(s) 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].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 May 2023

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

IDEAS '23

IDEAS '23: International Database Engineered Applications Symposium Conference

May 5 - 7, 2023

Heraklion, Crete, Greece

Acceptance Rates

Overall Acceptance Rate 74 of 210 submissions, 35%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
184
Total Downloads

Downloads (Last 12 months)82
Downloads (Last 6 weeks)1

Reflects downloads up to 13 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Fu YZhou MZhang L(2024)DAM: A Universal Dual Attention Mechanism for Multimodal Timeseries Cryptocurrency Trend Forecasting2024 IEEE International Conference on Metaverse Computing, Networking, and Applications (MetaCom)10.1109/MetaCom62920.2024.00025(73-80)Online publication date: 12-Aug-2024
https://doi.org/10.1109/MetaCom62920.2024.00025

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten