Spray and Pray is a speculative animated documentary that examines monetized disinformation infrastructures known as mushroom websites. These are networks of automatically generated news sites designed to launder misleading content and generate advertising revenue. The project focuses on the human-machine arrangements behind these infrastructures: platform users recruited to spread links for micro-payments, domain operators managing large clusters of websites, advertising intermediaries, and algorithmic systems that amplify circulation. Instead of framing disinformation as a purely technical problem, the film traces how automation, human labor, and economic incentives are entangled in producing scalable influence.

Developed through long-term research since 2023, the project draws on investigative journalism, academic reports, media-monitoring data, and collaboration with machine-learning researchers. Bulgarian-language disinformation content, an underrepresented area in AI-based detection, plays a central role, pointing to regional asymmetries in technological oversight and political exposure. Machine-learning models were applied to analyze headlines collected from mushroom websites, testing machine-generated text detection, disinformation likelihood, and sentiment. These experiments were not intended to provide definitive proof, but to inform the film's structure by foregrounding the limits of automated analysis.

The film adopts a hybrid documentary form in which research material is translated into cinematic situations. Characters are composed from anonymized data and performed roles, while synthetic voices and animation echo the mediated authorship of the systems portrayed. One fictional figure, the mushroom, speaks only through collected headlines, acting as a voice of the network itself.
In Spray and Pray, speculation becomes a form of evidence, tracing opaque infrastructures in which agency, authorship, and responsibility are continuously displaced.

Concept, direction, animation, editing, and production: Veneta Androva
Machine learning support: Tsvetomila Mihaylova
Sound design: Daniel Windisch
Mix and mastering: Sibin Vassilev
Bulgarian language models: The Big Data for Smart Society Institute (GATE), Sofia
Machine learning models used: BuST; bert_desinform_bg; sm_feel_bg; Eleven Multilingual v2
Synthetic voice contributors: Marta Djourina; Asparuh Donchev; Kiril Anchev; Bojidar Kassabov; Liusi Stavreva
Expert consultation: Veronika Dimitrova; Martin Stamenov
Subtitle adaptation: Rosanna Lovell; Alice Escher
With support from: FFA German Federal Film Funding - Reference Film Funding for Development (Short Film); Bulgarian Fund for Women, within the program “Fund for Artistic Projects by Women”

Veneta Androva (BG) is a visual artist and filmmaker based between Berlin and Sofia. Working with CGI-based moving image, documentary research, and speculative forms, she investigates how technological systems shape perception, political reality, and collective imagination. Her works are shown internationally across film festivals and exhibition contexts. In 2026, Spray and Pray premiered at Visions du Réel and is presented as part of the Bulgarian Pavilion at La Biennale di Venezia. Her film AIVA received an Award of Distinction at Prix Ars Electronica 2021.

Fake news and propaganda websites operate with particular ease in Bulgaria: lax legislation has enabled these emerging sites to spring up like mushrooms, becoming a lucrative business for operators and paid armies of trolls. Simultaneously, AI-based detection proves far less effective in Bulgarian than in other languages, allowing mass right-wing propaganda to frequently slip under the radar. With her extraordinary animated documentary, as humorous as its content is repulsive, Veneta Androva explores the human-machine interface. By deploying fictional yet thoroughly researched animated characters, particularly a smug, plum mushroom-man reading utterly absurd headlines, Spray and Pray lays bare the economic and political mechanisms of the lucrative business of anti-democratic subversion.