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Beyond detection: How Serbia's SNS party mimics authentic support through coordinated inauthentic behaviour

Ana Jovanovic-Harrington & Alessio Cornia

European Journal of Communication2026https://doi.org/10.1177/02673231261422076article
ABDC B
Weight
0.37

Abstract

As digital authoritarianism evolves, new tools are needed to analyse its increasingly subtle forms. This paper adopts a longitudinal analysis of under-explored secondary sources to examine coordinated inauthentic behaviour (CIB) linked to Serbia's ruling party, Serbian Progressive Party (SNS). Unlike centralised bot farms common in autocratic regimes, SNS networks evade detection longer and more effectively mimic authentic support. Drawing on sources rarely translated into English and often at risk of censorship, we contextualise these findings within the framework of third-wave autocratisation. Our research reveals that SNS coordinates CIB through public-sector personnel co-optation, leveraging state employment to incentivise participation. This form of organisation is under-explored in CIB literature. For this reason, this study offers new insights into how modern autocracies adapt their influence strategies. Moreover, the paper highlights the need for diverse methodological approaches to improve the detection and understanding of evolving digital propaganda.

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https://doi.org/https://doi.org/10.1177/02673231261422076

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@article{ana2026,
  title        = {{Beyond detection: How Serbia's SNS party mimics authentic support through coordinated inauthentic behaviour}},
  author       = {Ana Jovanovic-Harrington & Alessio Cornia},
  journal      = {European Journal of Communication},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/02673231261422076},
}

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Beyond detection: How Serbia's SNS party mimics authentic support through coordinated inauthentic behaviour

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.