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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).
deception, disinformation, social media, Twitter, Bulgarian, Telegram
Twitter Data
deception, disinformation, social media, Twitter, Bulgarian, Telegram
Twitter Data
| 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). | 0 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 23 |

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