cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7614246
title: TRACES Bulgarian Twitter Dataset on Covid-19 Annotated with Linguistic Markers of Lies

description: This dataset has been created within Project TRACES (more information: https://traces.gate-ai.eu/). The dataset contains 61411 tweet IDs of tweets, written in Bulgarian, with annotations. The dataset can be used for general use or for building lies and disinformation detection applications. 


Note: this dataset is not fact-checked, the social media messages have been retrieved via keywords. For fact-checked datasets, see our other datasets.


The tweets (written between 1 Jan 2020 and 28 June 2022) have been collected via Twitter API under academic access in June 2022 with the following keywords:



	

	
(Covid OR коронавирус OR Covid19 OR Covid-19 OR Covid_19) - without replies and without retweets
	
	

	
(Корона OR корона OR Corona OR пандемия OR пандемията OR Spikevax OR SARS-CoV-2 OR бустерна доза) - with replies, but without retweets
	



Explanations of which fields can be used as markers of lies (or of intentional disinformation) are provided in our forthcoming paper (please cite it when using this dataset): 


Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology
Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
description: The project TRACES has indirectly received funding from the European Union's Horizon 2020 research and innovation action programme, via the AI4Media Open Call #1 issued and executed under the AI4Media project (Grant Agreement no. 951911).

This resource is shared with the License: Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0).

The texts should not be used for user profiling.

The Project Sponsors (European Commission and the AI4Media project), Researchers, users or subjects shall not be liable or otherwise responsible for any damages (including pecuniary or moral damages) arising out or in relation to the uses of this resource.

When using this resource, please cite this article:

Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
DOI: 10.5281/zenodo.7614247
title: TRACES Bulgarian Twitter Dataset on Covid-19 Annotated with Linguistic Markers of Lies

description: This dataset has been created within Project TRACES (more information: https://traces.gate-ai.eu/). The dataset contains 61411 tweet IDs of tweets, written in Bulgarian, with annotations. The dataset can be used for general use or for building lies and disinformation detection applications. 


Note: this dataset is not fact-checked, the social media messages have been retrieved via keywords. For fact-checked datasets, see our other datasets.


The tweets (written between 1 Jan 2020 and 28 June 2022) have been collected via Twitter API under academic access in June 2022 with the following keywords:



	

	
(Covid OR коронавирус OR Covid19 OR Covid-19 OR Covid_19) - without replies and without retweets
	
	

	
(Корона OR корона OR Corona OR пандемия OR пандемията OR Spikevax OR SARS-CoV-2 OR бустерна доза) - with replies, but without retweets
	



Explanations of which fields can be used as markers of lies (or of intentional disinformation) are provided in our forthcoming paper (please cite it when using this dataset): 


Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology
Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
description: The project TRACES has indirectly received funding from the European Union's Horizon 2020 research and innovation action programme, via the AI4Media Open Call #1 issued and executed under the AI4Media project (Grant Agreement no. 951911).

This resource is shared with the License: Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0).

The texts should not be used for user profiling.

The Project Sponsors (European Commission and the AI4Media project), Researchers, users or subjects shall not be liable or otherwise responsible for any damages (including pecuniary or moral damages) arising out or in relation to the uses of this resource.

When using this resource, please cite this article:

Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
DOI: 10.5281/zenodo.7614317
title: TRACES Bulgarian Twitter Dataset on Lies and Manipulation Annotated with Linguistic Markers of Lies

description: This dataset has been created within Project TRACES (more information: https://traces.gate-ai.eu/). The dataset is in .csv format and contains 32518 tweet IDs of tweets, written in Bulgarian, with annotations. Note: this dataset is not fact-checked, the social media messages have been retrieved via keywords. For fact-checked datasets, see our other datasets.


The dataset can be used for general purposes or for building lies and disinformation detection applications (by using the annotations with the linguistic markers of lies). 


The tweets (written between 1 Jan 2020-27 June 2022) have been collected via Twitter API under academic access in June-July 2022 with the following keywords:


(лъжа OR лъжи OR лицемерие OR лъжат OR излъга OR измама OR измамници OR измами OR лъжец OR лъжци) 


(фалшиви OR fakenews OR невярно OR неверни OR подвеждащи OR подвеждащо OR неистини) - without retweets


(манипулация OR манипулира OR стъкмистика OR крие OR далавераджия OR далавери OR далавера) - without retweets


Explanation of which fields can be used as markers of lies (or of intentional disinformation) are provided in our forthcoming paper:


Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology
Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.


 
description: The project TRACES has indirectly received funding from the European Union's Horizon 2020 research and innovation action programme, via the AI4Media Open Call #1 issued and executed under the AI4Media project (Grant Agreement no. 951911).

This resource is shared with the License: Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0).

We forbid the use of these texts for:



user profiling


The Project Sponsors (European Commission and the AI4Media project), Researchers, users or subjects shall not be liable or otherwise responsible for any damages (including pecuniary or moral damages) arising out or in relation to the uses of this resource.

When using this resource, please cite this article:

Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
DOI: 10.5281/zenodo.7614318
title: TRACES Bulgarian Twitter Dataset on Lies and Manipulation Annotated with Linguistic Markers of Lies

description: This dataset has been created within Project TRACES (more information: https://traces.gate-ai.eu/). The dataset is in .csv format and contains 32518 tweet IDs of tweets, written in Bulgarian, with annotations. Note: this dataset is not fact-checked, the social media messages have been retrieved via keywords. For fact-checked datasets, see our other datasets.


The dataset can be used for general purposes or for building lies and disinformation detection applications (by using the annotations with the linguistic markers of lies). 


The tweets (written between 1 Jan 2020-27 June 2022) have been collected via Twitter API under academic access in June-July 2022 with the following keywords:


(лъжа OR лъжи OR лицемерие OR лъжат OR излъга OR измама OR измамници OR измами OR лъжец OR лъжци) 


(фалшиви OR fakenews OR невярно OR неверни OR подвеждащи OR подвеждащо OR неистини) - without retweets


(манипулация OR манипулира OR стъкмистика OR крие OR далавераджия OR далавери OR далавера) - without retweets


Explanation of which fields can be used as markers of lies (or of intentional disinformation) are provided in our forthcoming paper:


Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology
Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.


 
description: The project TRACES has indirectly received funding from the European Union's Horizon 2020 research and innovation action programme, via the AI4Media Open Call #1 issued and executed under the AI4Media project (Grant Agreement no. 951911).

This resource is shared with the License: Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0).

We forbid the use of these texts for:



user profiling


The Project Sponsors (European Commission and the AI4Media project), Researchers, users or subjects shall not be liable or otherwise responsible for any damages (including pecuniary or moral damages) arising out or in relation to the uses of this resource.

When using this resource, please cite this article:

Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
DOI: 10.15468/dl.cdyakk
title: Occurrence Download

description: A dataset containing 2137 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vulpes macrotis Merriam, 1888",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2137 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015512-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.7614293
title: TRACES Bulgarian Telegram Dataset Annotated with Linguistic Markers of Lies

description: This dataset has been created within Project TRACES (more information: https://traces.gate-ai.eu/). The dataset contains 8791 anonymized Telegram social media posts, written in Bulgarian. The dataset is annotated with general information (named entities, part-of-speech tags, sentence length, etc.) and specific markers signaling details and can be used for general purposes or for building lies, manipulation, and disinformation detection applications. 


Note: this dataset is not fact-checked, the social media messages have been retrieved via keywords. For fact-checked datasets, see our other datasets.


The social media posts have been collected via Telegram Desktop in June-July 2022.


Explanations of which fields can be used as markers of lies (or of intentional disinformation) are provided in our forthcoming paper: 


Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology
Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
description: The project TRACES has indirectly received funding from the European Union's Horizon 2020 research and innovation action programme, via the AI4Media Open Call #1 issued and executed under the AI4Media project (Grant Agreement no. 951911).

 

This dataset is shared with the License: Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0).

We forbid the use of these texts for:



user profiling


The Project Sponsors (European Commission and the AI4Media project), Researchers, users or subjects shall not be liable or otherwise responsible for any damages (including pecuniary or moral damages) arising out or in relation to the uses of this resource.

When using this resource, please cite this article:

Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
DOI: 10.5281/zenodo.7614294
title: TRACES Bulgarian Telegram Dataset Annotated with Linguistic Markers of Lies

description: This dataset has been created within Project TRACES (more information: https://traces.gate-ai.eu/). The dataset contains 8791 anonymized Telegram social media posts, written in Bulgarian. The dataset is annotated with general information (named entities, part-of-speech tags, sentence length, etc.) and specific markers signaling details and can be used for general purposes or for building lies, manipulation, and disinformation detection applications. 


Note: this dataset is not fact-checked, the social media messages have been retrieved via keywords. For fact-checked datasets, see our other datasets.


The social media posts have been collected via Telegram Desktop in June-July 2022.


Explanations of which fields can be used as markers of lies (or of intentional disinformation) are provided in our forthcoming paper: 


Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology
Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
description: The project TRACES has indirectly received funding from the European Union's Horizon 2020 research and innovation action programme, via the AI4Media Open Call #1 issued and executed under the AI4Media project (Grant Agreement no. 951911).

 

This dataset is shared with the License: Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0).

We forbid the use of these texts for:



user profiling


The Project Sponsors (European Commission and the AI4Media project), Researchers, users or subjects shall not be liable or otherwise responsible for any damages (including pecuniary or moral damages) arising out or in relation to the uses of this resource.

When using this resource, please cite this article:

Irina Temnikova, Silvia Gargova, Ruslana Margova, Veneta Kireva, Ivo Dzhumerov, Tsvetelina Stefanova and Hristiana Nikolaeva (2023) New Bulgarian Resources for Detecting Disinformation. 10th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics (LTC'23). Poznań. Poland.
DOI: 10.15468/dl.qjpz3a
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aedes albopictus (Skuse, 1894)",
 "Country is Argentina",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 14 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015516-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2rvtjn
title: Occurrence Download

description: A dataset containing 1184 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vulpes velox (Say, 1823)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1184 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015517-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7266/x9bcqkmm
title: Survey dataset of wintering waterfowl use of marsh terraces and non-terraced sites in the northern Gulf of Mexico from 2018-10-11 to 2020-03-05
DOI: 10.15468/dl.6jn5zz
title: Occurrence Download

description: A dataset containing 22127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Orcinus Fitzinger, 1860"
 ]
}

 The dataset includes 22127 records from 353 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015525-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p68wt6
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "TaxonKey is Fumaria indica (Hausskn.) Pugsley"
 ]
}

 The dataset includes 40 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001902-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a49afw
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "OccurrenceStatus is Present",
 "TaxonKey is Avellara fistulosa (Brot.) Blanca & C.Díaz"
 ]
}

 The dataset includes 18 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001903-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aqwdp2
title: Occurrence Download

description: A dataset containing 94105 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "DatasetKey is one of (EOD – eBird Observation Dataset, iNaturalist Research-grade Observations, Actualización y depuración de la base de datos del Herbario del Instituto de Ecología, AC, Centro Regional del Bajío. Fase 2)",
 "Geometry POLYGON((-101.44809 20.80465,-101.5747 20.67537,-101.56937 20.45015,-101.43076 20.37818,-101.07094 20.34886,-100.3766 20.37552,-100.36194 20.56743,-100.37394 20.72468,-100.57251 20.74201,-100.92967 20.82064,-101.44809 20.80465))",
 "PublishingOrg is one of (e2e717bf-551a-4917-bdc9-4fa0f342c530, 28eb1a3f-1c15-4a95-931a-4af90ecb574d, ff90b050-c256-11db-b71b-b8a03c50a862, b459e790-0d3c-11d9-8431-b8a03c50a862)",
 "Year 1985-2025"
 ]
}

 The dataset includes 94105 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001887-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g32zfk
title: Occurrence Download

description: A dataset containing 687 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Baccharis spicata (Lam.) Baill.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 687 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001905-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uw3bjh
title: Occurrence Download

description: A dataset containing 776 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Elachistocleis bicolor (Guérin-Méneville, 1838)",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 776 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001904-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ayb7he
title: Occurrence Download

description: A dataset containing 747 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Elleanthus graminifolius (Barb.Rodr.) Løjtnant"
 ]
}

 The dataset includes 747 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001955-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14951506
title: costus_obscurus_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.14951507
title: costus_obscurus_decontaminated_FSCR.fasta.gz
DOI: 10.15468/dl.9q8s4r
title: Occurrence Download

description: A dataset containing 2625 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eleutherodactylus coqui Thomas, 1966",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 2625 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001907-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5xbwdr
title: Occurrence Download

description: A dataset containing 655 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bacopa rotundifolia (Michx.) Wettst.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 655 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001908-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fn98ak
title: Occurrence Download

description: A dataset containing 51585 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Daedaleopsis confragosa (Bolton) J.Schröt."
 ]
}

 The dataset includes 51585 records from 444 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001900-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.