Advanced social media sentiment analysis for short‐term cryptocurrency price prediction

Wołk, Krzysztof

doi:10.1111/exsy.12493

Cited by 91 publications

(76 citation statements)

References 25 publications

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“…They show that a bi-directional causal relationship between Bitcoin attention and Bitcoin returns is well-documented. Wołk (2019) analyzes the impact of social media on cryptocurrency prices. In this regard, Twitter and Google Trends are used in order to predict the short-term prices of digital currencies given that such social media platforms are employed to affect purchasing decisions.…”

Section: What Do You Learn About Social Media Bitcoin and Covid-19 Pandemic?mentioning

confidence: 99%

A short-and long-term analysis of the nexus between Bitcoin, social media and Covid-19 outbreak

Béjaoui¹,

Mgadmi²,

Moussa³

et al. 2021

Heliyon

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In this paper, we attempt to analyze the dynamic interplay between Bitcoin, social media, and the Covid-19 health crisis. For this end, we apply the fractional autoregressive vector model, fractional error correction model and impulse response functions on daily data over the period 31/12/2019-30/10/2020. Our results clearly show the short- and long-term evidence of the nexus between the Bitcoin price, social media metrics (Tweets and Google Trends) and the intensity of the Covid-19 pandemic. As well, the Covid-19 pandemic does not impact on social media metrics in the short- and long-term. On the other hand, the Covid-19 pandemic positively affects social media metrics. Also, the Covid-19 pandemic encourages investing in digital currencies such as Bitcoin. So, the Covid-19 health crisis significantly influences social media networks and Bitcoin prices.

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Section: What Do You Learn About Social Media Bitcoin and Covid-19 Pandemic?mentioning

confidence: 99%

A short-and long-term analysis of the nexus between Bitcoin, social media and Covid-19 outbreak

Béjaoui¹,

Mgadmi²,

Moussa³

et al. 2021

Heliyon

View full text Add to dashboard Cite

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“…Indeed, this is only a minimal estimate, which is highly dependent on the volatility of cryptocurrency prices and network load. 13 In the past, there were cases where a budget restriction of the decentralized system would not allow transactions to take place for several months or would have greatly exceeded that budget. In addition, the minimum value obtained does not consider the cost of any additional logic other than the plain write of the data obtained from experts and secure interaction through transaction delegation.…”

Section: Cost Estimationmentioning

confidence: 99%

A Cost-Effective Approach to Securing Systems through Partial Decentralization

Savchenko¹,

Tsyganok²,

Andriichuk³

2020

ISIJ

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A study has been conducted on the methods of secure computation and storage decentralization, based on expert and decision support systems' needs. It identified the common disadvantages of modern, Distributed Ledger Technologybased (DLT-based) decentralized systems and suggested a solution to it-the universal transaction delegation method. This method eliminates the complexity of a decentralized system from end-users' point of view, which during the study was identified as the main disadvantage of DLT-based systems. This article provides a brief overview of existing approaches to solve the usage complexity problem, based on data from well-known projects built with Ethereum, the leading DLT-based smart contract platform. As a result of the research, we implemented the universal transaction delegation method which does not depend on the signature standard used in the decentralized program. In addition, we present results of an experimental economic analysis of the solution based on real network tests and data as of 2020.

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“…Sentiment analysis using Twitter and Google Trends forms another new tool to forecast Bitcoin prices. For instance, Wołk [58] recently mobilized this computational tool to predict the prices of Bitcoin and other cryptocurrencies for different time intervals. The author highlights that people's psychological and behavioral attitudes significantly impact the highly speculative cryptocurrency prices.…”

Section: Introductionmentioning

confidence: 99%

Is It Possible to Forecast the Price of Bitcoin?

2021

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This paper focuses on forecasting the price of Bitcoin, motivated by its market growth and the recent interest of market participants and academics. We deploy six machine learning algorithms (e.g., Artificial Neural Network, Support Vector Machine, Random Forest, k-Nearest Neighbours, AdaBoost, Ridge regression), without deciding a priori which one is the ‘best’ model. The main contribution is to use these data analytics techniques with great caution in the parameterization, instead of classical parametric modelings (AR), to disentangle the non-stationary behavior of the data. As soon as Bitcoin is also used for diversification in portfolios, we need to investigate its interactions with stocks, bonds, foreign exchange, and commodities. We identify that other cryptocurrencies convey enough information to explain the daily variation of Bitcoin’s spot and futures prices. Forecasting results point to the segmentation of Bitcoin concerning alternative assets. Finally, trading strategies are implemented.

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Advanced social media sentiment analysis for short‐term cryptocurrency price prediction

Cited by 91 publications

References 25 publications

A short-and long-term analysis of the nexus between Bitcoin, social media and Covid-19 outbreak

A short-and long-term analysis of the nexus between Bitcoin, social media and Covid-19 outbreak

A Cost-Effective Approach to Securing Systems through Partial Decentralization

Is It Possible to Forecast the Price of Bitcoin?

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