Performance Comparison of LSTM and XGBOOST for Ether Price Prediction from Spam Filtered Tweets-Reference-Cited by-同舟云学术

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Performance Comparison of LSTM and XGBOOST for Ether Price Prediction from Spam Filtered Tweets

Published:2023-02-09 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS)
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Author:

Sathiyapriya K.¹,Vankadara Sravya¹,Babu Kumaresh Suresh¹,Muralidharan Mridula¹

Affiliation:

1. PSG College of Technology,Computer Science and Engineering,Coimbatore,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10099476/10100336/10100425.pdf?arnumber=10100425

Reference20 articles.

1. A Stacking Ensemble Deep Learning Model for Bitcoin Price Prediction Using Twitter Comments on Bitcoin

2. Cryptocurrency price prediction using tweet volumes and sentiment analysis;abraham;SMU Data Science Review,2018

3. A Comprehensive Study on Lexicon Based Approaches for Sentiment Analysis

4. VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text

5. Cross Cryptocurrency Relationship Mining for Bitcoin Price Prediction

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Foggier skies, clearer clouds: A real-time IoT-DDoS attack mitigation framework in fog-assisted software-defined cyber-physical systems;Computers & Security;2024-04

2. A Deep Learning based Model for Predicting the future prices of Bitcoin;2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN);2023-05-05

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