Supervised Classification Methods for Fake News Identification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F20%3A63527099" target="_blank" >RIV/70883521:28140/20:63527099 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-61534-5_40" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-61534-5_40</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-61534-5_40" target="_blank" >10.1007/978-3-030-61534-5_40</a>
Alternative languages
Result language
angličtina
Original language name
Supervised Classification Methods for Fake News Identification
Original language description
Along with the rapid increase in the popularity of onlinemedia, the proliferation of fake news and its propagation is also rising.Fake news can propagate with an uncontrollable speed without verifica-tion and can cause severe damages. Various machine learning and deeplearning approaches have been attempted to classify the real and thefalse news. In this research, the author group presents a comprehensiveperformance evaluation of eleven supervised algorithms on three datasetsfor fake news classification.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-303061533-8
ISSN
03029743
e-ISSN
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Number of pages
10
Pages from-to
445-454
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Berlín
Event location
Zakopane
Event date
Oct 12, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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