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Dataset . 2023
Data sources: Datacite
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Dataset . 2023
Data sources: Datacite
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TRACES Telegram and Twitter Dataset with Bulgarian Journalists Manual Annotations of True/Untrue and Disinformation/Not and Automatic Annotations for Markers of Lies

Authors: Temnikova, Irina; Gargova, Silvia; Margova, Ruslana; Kireva, Veneta; Tsvetelina Stefanova;

TRACES Telegram and Twitter Dataset with Bulgarian Journalists Manual Annotations of True/Untrue and Disinformation/Not and Automatic Annotations for Markers of Lies

Abstract

TRACES dataset of 4083 Twitter and Telegram posts automatically annotated for markers of lies and manually by Bulgarian journalists for containing true/untrue information and disinformation or not. Each message has been annotated by usually 3 (in under 10 cases by 2 annotators). The annotators came from different media, in order to obtain various views. They were asked to not get biased and were assured that their identities will not be revealed. The dataset is a subset of these other datasets: https://zenodo.org/record/7614247 https://zenodo.org/record/7614318 https://zenodo.org/record/7614357 https://zenodo.org/record/7614294 It has been annotated following these Annotation Guidelines: https://zenodo.org/record/7706743

This dataset was collected and annotated during the project TRACES, which 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).

Keywords

deception, disinformation, social media, Twitter, Bulgarian, Telegram

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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