Cryptocurrency Price Prediction using Time Series And Social Sentiment…
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ContentsBDCAT '19: Proceedings of the sixth IEEE/ACM International Conference on Big Data Computing, Applications and TechnologiesCryptocurrency Price Prediction utilizing Time Series and Social Sentiment DataPages 35 - forty one
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Index Terms
Cryptocurrency Price Prediction using Time Series and Social Sentiment DataApplied computing
Operations analysis
Forecasting
Information methods
Information retrieval
Retrieval tasks and targets
Sentiment evaluation
Information methods functions
Data mining
Association guidelines
Mathematics of computing
Probability and statistics
Statistical paradigms
Time collection analysis
Security and privacy
Cryptography
Symmetric cryptography and hash features
Hash functions and message authentication codes
Theory of computation
Theory and algorithms for software domains
Machine learning theory
Structured prediction
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General Chairs:
Kenneth JohnsonAuckland University of Technology, New Zealand
,
Josef SpillnerZurich University of Applied Sciences, Switzerland
,
Program Chairs:
Xinghui ZhaoWashington State University, USA
,
Olga DatskovaCERN, Switzerland
,
Blesson VargheseQueen's University Belfast, UK
Sponsors
SIGARCH: ACM Special Interest Group on Computer Architecture
- IEEE TCSC: IEEE Technical Committee on Scalable Computing
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Association for Computing Machinery
New York, NY, United States
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Author Tags
algorithmic buying and selling
bitcoin
cryptocurrency
sentiment analytics
time series analysis
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Roumeliotis KTselikas NNasiopoulos D(2024)LLMs and NLP Models in Cryptocurrency Sentiment Analysis: A Comparative Classification StudyBig Data and Cognitive Computing10.3390/bdcc80600638:6(63)Online publication date: 5-Jun-2024https://doi.org/10.3390/bdcc8060063
Jain SJohari SDelhibabu R(2024)The future of Cryptocurrency Market Analysis: Social Media Data and User Meta-DataLobachevskii Journal of Mathematics10.1134/S199508022460071745:3(1160-1174)Online publication date: 19-Jul-2024https://doi.org/10.1134/S1995080224600717
Chandra DTyagi PGupta RSaxena AKharaliya S(2024)Cryptocurrency Price Prediction utilizing Machine Learning2024 2nd International Conference on Advancement in Computation & Computer Technologies (InCACCT)10.1109/InCACCT61598.2024.10551043(258-264)Online publication date: 2-May-2024https://doi.org/10.1109/InCACCT61598.2024.10551043
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Saraswathi RBollina SBongu RCherukuru AChintala N(2023)A Novel LSTM primarily based Approach for Crypto Currency Price Prediction2023 International Conference on Sustainable Communication Networks and Application (ICSCNA)10.1109/ICSCNA58489.2023.10370544(1-6)Online publication date: 15-Nov-2023https://doi.org/10.1109/ICSCNA58489.2023.10370544
Shrotriya LKhatwani RMishra MShah PBadala JChinmulgund ABedarkar MSekhar R(2023)Cryptocurrency Algorithmic Trading with Price Forecasting Analysis using PowerBI2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI)10.1109/ICAEECI58247.2023.10370932(1-6)Online publication date: 19-Oct-2023https://doi.org/10.1109/ICAEECI58247.2023.10370932
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Kim DLee MKi WKim D(2022)Exploring the Role of User-Driven Communities in NFT Valuation: A Case Study of DiscordJournal of Multimedia Information System10.33851/JMIS.2022.9.4.2999:4(299-314)Online publication date: 31-Dec-2022https://doi.org/10.33851/JMIS.2022.9.4.299
Žunić ADželihodžić A(2022)Predicting the worth of Cryptocurrencies Using Machine Learning AlgorithmsAdvanced Technologies, Systems, and Applications VII10.1007/978-3-031-17697-5_33(412-425)Online publication date: 16-Oct-2022https://doi.org/10.1007/978-3-031-17697-5_33
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