JOURNAL ARTICLE
STRANGE BIRDS IN SONG-CAGES (FROM RADIO "PARROTS" TO IINTERNET "TURKEYS": THE FUNNY AND THE HILARIOUS IN THE NEXUS OF THE POPULAR AND THE POLITICAL IN MEDIA MUSIC FROM BULGARIA).
Published In: Sociological Problems, 2025, v. 57. P. 92 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Dimov, Ventsislav 3 of 3
Abstract
This article explores the intersections of popular, political, media, music, and funny as metareferences in Bulgarian media over the last one hundred years. It draws parallels between the intermedial representation of pop politics as pop culture across three different periods, each with its typical media: the 1920s with Stoyan Milenkov’s couplet songs and political cabaret, and the newspaper Papagal (Parrot); Milenkov’s political propaganda couplets and the radio "Parrot" after 1944; and the post-1989 waves of Bulgarian hip-hop – encompassing rap as a performing art, radio freestyles, and YouTube comedy rap videos – and the political satirical cartoons in the newspaper Pras-Press. The conclusions are that the paths of the song-poetic-political-popular in Bulgarian media music – from the coupletists to contemporary rappers, and from radio to video-sharing platforms – run through the funny and the hilarious. In today’s nexus of the popular and the political, the satirical rap song is a shared narrative between artists and audience. Themes, poetics, and vocabulary navigate various registers of the funny: Bulgarian socially and politically conscious rap – whether serious or parodic – is witty and angry, sarcastic and darkly funny, caustic and carnivalesque. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Sociological Problems. 2025/01, Vol. 57, p92
- Document Type:Article
- Subject Area:Drama and Theater Arts
- Publication Date:2025
- ISSN:0324-1572
- Accession Number:190580133
- Copyright Statement:Copyright of Sociological Problems is the property of Bulgarian Academy of Sciences, Institute for the Study of Societies & Knowlegde and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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