| dc.contributor.author |
Amilevičius, Darius |
| dc.contributor.author |
Utka, Andrius |
| dc.contributor.author |
Meidutė, Aistė |
| dc.contributor.author |
Ruzaitė, Jūratė |
| dc.date.accessioned |
2023-02-20T09:42:05Z |
| dc.date.available |
2023-02-20T09:42:05Z |
| dc.date.issued |
2023-02-20 |
| dc.identifier.uri |
http://hdl.handle.net/20.500.11821/54 |
| dc.description |
DIGIRES COVID-19 ML dataset v.1 is a tab-separated (.tsv) file prepared for training machine learning algorithms. The training dataset was compiled from various internet public Lithuanian media sources. It contains 351 records and has the following attributes:
"Title": the title of a news article
"Text": the text of the article
"Label": a label that marks the article as 1: unreliable; 0: reliable
1) "unrealiable" marks articles, which were identified by professional fact checkers as fake news; 2) "reliable" marks trustworthy articles.
Classes Labels Word tokens
Reliable: 175 67902
Unreliable: 176 118747
Total 351 186649 |
| dc.language.iso |
lit |
| dc.publisher |
Vytautas Magnus University |
| dc.rights |
PUB_CLARIN-LT_End-User-Licence-Agreement_EN-LT |
| dc.rights.uri |
https://clarin.vdu.lt/licenses/eula/PUB_CLARIN-LT_End-User-Licence-Agreement_EN-LT.htm |
| dc.rights.label |
PUB |
| dc.source.uri |
https://digires.lt/ |
| dc.subject |
fake news detection |
| dc.subject |
machine learning |
| dc.title |
DIGIRES COVID-19 ML Dataset v.1 |
| dc.type |
toolService |
| metashare.ResourceInfo#ContentInfo.detailedType |
nlpDevelopmentEnvironment |
| metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent |
true |
| hidden |
false |
| hasMetadata |
false |
| has.files |
yes |
| branding |
CLARIN-LT |
| contact.person |
Andrius Utka andrius.utka@vdu.lt Vytautas Magnus University |
| contact.person |
Darius Amilevičius darius.amilevicius@vdu.lt Vytautas Magnus University |
| sponsor |
European Commission LC-01682259 DIGIRES - Supporting Collaborative Partnerships for Digital Resilience and Capacity Building in the Times of Disinfodemic/COVID-19 euFunds |
| files.size |
545232 |
| files.count |
2 |
