Forecasting Cryptocurrency Value by Sentiment Analysis


Case Study Team

Coordinators

Id Name Institution (type*) Contact e-mail Related WG Role in the team
1  Aleš Zamuda  University of Maribor, SI  ales.zamuda@um.si   WG4 Coordinator
2 Andrea Bracciali University of Stirling, UK  (A) abb@cs.stir.ac.uk WG3 Vice-Coordinator

Team Members

Id Name Institution (type*) Contact e-mail Related WG
1 Vasco Amaral Nova University of Lisbon, PT (A) vasco.amaral@gmail.com WG2
2 Joana Matos Dias   Universidade de Coimbra, PT (A) joana@fe.uc.pt WG4
3 José Covelo García  Luckia Gaming Group, ES (I) jose.covelo.garcia@gmail.com WG4
4 Horacio Gonzalez-Velez National College of Ireland, IE (A) Horacio.Gonzalez-Velez@ncirl.ie WG1
5 Miguel Goulão Universidade Nova de Lisboa, PT (A) mgoul@fct.unl.pt WG4
6 Mariam Kiran ESNet, UK (I) mariam.kiran@gmail.com WG4
7  Roman Šenkeřík  University Tomas-Bata, Zlin CZ (A) senkerik@utb.cz WG4
8 Katarzyna Wegrzyn-Wolska ESIGETEL, FR (A)  katarzyna.wegrzyn@groupe-efrei.fr WG4
9  Juan C. Burguillo-Rial (A) Universidade de Vigo, ES (A)  J.C.Burguillo@uvigo.es WG4

*A-academia, I-industry


Addressed Problem

Aim: The aim of the case study is to find the correlations between sentiments and blockchain technologies.

Topics: Text mining, Sentiment analysis, Blockchain technologies for e-currencies, ICO – Initial Coin Offerings

Main Problem: Forecasting crypto-currency assets’ value


Existing Solution(-s) (Models, Tools)

TBC


 Proposed Solution(-s) (Models, Tools)

TBC


Practical Scenarios (-s)

TBC


Supplementary Material

TBC