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ZENODO
Preprint . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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Disinformation on social media in Latvia (September 2022 – March 2023)

Authors: Locmele, Klinta; Skolmeistere, Velta;

Disinformation on social media in Latvia (September 2022 – March 2023)

Abstract

The article examines disinformation on social media (mainly Twitter and TikTok) in the Latvian language to identify the topics and frequency of disinformation, the types of arguments used, and the specific dissemination patterns. A content analysis of 200 posts reveals a disinformation's extensive focus on the politics of Latvia, as well as international events and trends. Furthermore, it shows a lack of argumentation as a regularity, as well as differences between the narratives on Twitter and Tiktok.

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Keywords

disinformation, TikTok, social media, Instagram, misinformation, Social Media

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
0
Average
Average
Average
Green
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