TY - GEN
T1 - Bitcoin Price Prediction Considering Sentiment Analysis on Twitter and Google News
AU - Youssfi Nouira, Ameni
AU - Bouchakwa, Mariam
AU - Jamoussi, Yassine
N1 - Publisher Copyright:
© 2023 ACM.
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PY - 2023/5/5
Y1 - 2023/5/5
N2 - 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.
AB - 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.
KW - Google news data
KW - LSTM
KW - machine learning
KW - price bitcoin prediction
KW - Sentiment Analysis
KW - Tweets
UR - http://www.scopus.com/inward/record.url?scp=85161386087&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85161386087&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/006983bd-bf9f-3690-b8fe-965f59e60588/
U2 - 10.1145/3589462.3589494
DO - 10.1145/3589462.3589494
M3 - Conference contribution
AN - SCOPUS:85161386087
SN - 9798400707445
T3 - International Database Engineered Applications Symposium Conference
SP - 71
EP - 78
BT - ACM International Conference Proceeding Series
A2 - Chbeir, Richard
A2 - Ivanovic, Mirjana
A2 - Manolopoulos, Yannis
A2 - Revesz, Peter Z.
PB - Association for Computing Machinery
T2 - 27th International Database Engineered Applications Symposium, IDEAS 2023
Y2 - 5 May 2023 through 7 May 2023
ER -