Database comments on Telegram channels related to cryptocurrencies with sentiments. [PDF]
Jahanbin K +3 more
europepmc +1 more source
Counterfactual Explanation-Based Cryptocurrency Price Prediction. [PDF]
Luo X, Yin W.
europepmc +1 more source
Measurement, Characterization, and Mapping of COVID-19 Misinformation in Spain: Cross-Sectional Study. [PDF]
Alvarez-Galvez J +11 more
europepmc +1 more source
Psycholinguistic and emotion analysis of cryptocurrency discourse on X platform. [PDF]
Tash MS +3 more
europepmc +1 more source
Electricity and cryptocurrency mining: An empirical contribution. [PDF]
Okorie DI, Gnatchiglo JM, Wesseh PK.
europepmc +1 more source
A swarm-optimization based fusion model of sentiment analysis for cryptocurrency price prediction. [PDF]
Tiwari D +5 more
europepmc +1 more source
Decoding the cryptocurrency user: An analysis of demographics and sentiments. [PDF]
Campino J, Yang S.
europepmc +1 more source
The political, psychological, and social correlates of cryptocurrency ownership. [PDF]
Littrell S, Klofstad C, Uscinski JE.
europepmc +1 more source
Chapman-Kolmogorov test for estimating memory length of two coupled processes. [PDF]
Motahari H +3 more
europepmc +1 more source
Do consumers really trust cryptocurrencies?
Purpose: In this study, we focus on consumer perceptions of cryptocurrencies. We hypothesize that knowledge of cryptocurrencies, trust in government, and the speed of transactions are the main factors contributing to consumers' trust in cryptocurrencies.
Denni Arli +2 more
exaly +2 more sources

