Results

eNauka >  Rezultati >  AI alignment: Assessing the global impact of recommender systems
Naziv: AI alignment: Assessing the global impact of recommender systems
Autori: Bojic, Ljubisa  
Godina: 2024
Publikacija: Futures
ISSN: 0016-3287 Futures Pretraži identifikator
Izdavač: Elsevier
Tip rezultata: Naučni članak
Kolacija: vol. 160 br. 103383 str. 103383-103383
DOI: 10.1016/j.futures.2024.103383
WoS-ID: 001295378400001
Scopus-ID: 2-s2.0-85190864689
URI: https://rifdt.ifdt.bg.ac.rs/123456789/3816
http://rifdt.instifdt.bg.ac.rs/123456789/3816
https://enauka.gov.rs/handle/123456789/915069
Projekat: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HaDEA). Neither the European Union nor the granting authority can be held responsible for them. Grant Agreement no. 101120763 - TANGO.
This paper was realised with the support of the Ministry of Science, Technological Development and Innovation of the Republic of Serbia, according to the Agreement on the realisation and financing of scientific research: 451-03-66/2024-03/ 200025.
This paper has been supported by the TWin of Online Social Networks (TWON), a research project funded by the European Union, under the Horizon Europe framework (HORIZON-CL2–2022-DEMOCRACY-01, topic 07). TWON poject number is 101095095. More details can be found on its official website: https://www.twon-project.eu/.
This research has been accomplished with the support and collaboration from the COST Action Network CA21129 - What are Opinions? Integrating Theory and Methods for Automatically Analyzing Opinionated Communication (OPINION) - https://www.opinion-network.eu/.
M-kategorija: 
21aM21a - Vodeći međunarodni časopis kategorije M21a

18
SCOPUSTM
15
WEB OF SCIENCETM
Altmetric
Dimensions
Unpaywall

Creative Commons License