Sari la conținut

Română · beta. Traducerea a fost făcută automat și este încă în curs de revizuire. Citește pagina în engleză

perspectiva aiqbenchAI & societate

analiza aiqbench

This study applies computational linguistics and machine learning classifiers to analyze the political ideology of the German rock band Frei.Wild, achieving up to 97% accuracy in identifying right-wing extremist tendencies within their lyrics. By leveraging large language models and lexical analysis on a curated dataset, the research demonstrates how AI can effectively resolve borderline cases where manual monitoring fails to detect subtle ideological shifts. The work highlights the utility of NLP techniques for regulatory bodies seeking to automate the detection of radical content in music without relying solely on human review.
Sursă care acoperăarXiv
Ce este aceastaLectura unui model asupra articolului și a acoperirii conexe, scrisă pentru aiqbench. Nu sunt cuvintele publicației.

Right-Wing Rock or Just Rock? A Computational Linguistic Analysis of Frei.Wild

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2609.39460v1 Announce Type: new Abstract: Rechtsrock is a subgenre of rock music that spreads right-wing ideology, often instrumentalized to recruit adolescents into the radical scene. Monitoring institutions counteract this by manually examining and, in some cases, banning extremist content; however, there are border cases that evade regulation. We present a study aimed at determining whether such a case, the band Frei.Wild, should be classified as politically right-leaning or as part of the general German rock genre. We sampled a German rock dataset and created a corpus for right-wing rock to use as reference in this analysis and found that we can confirm the intuitions from previous investigations that Frei.Wild successfully maintains an ambiguity with regard to their political affiliation. However, the tendency is towards the right-wing spectrum. Lexical analyses reveal nationalistic narratives and two high-performing classifiers (up to 97% ROC-AUC score) label more than half of their songs as right-wing extremist. Our analysis provides insight into how computational methods can improve the process of identifying right-wing extremist tendencies in music, especially in borderline cases like Frei.Wild. The code and data are made available for future research.

Title:Right-Wing Rock or Just Rock? A Computational Linguistic Analysis of Frei.Wild

Abstract:Rechtsrock is a subgenre of rock music that spreads right-wing ideology, often instrumentalized to recruit adolescents into the radical scene. Monitoring institutions counteract this by manually examining and, in some cases, banning extremist content; however, there are border cases that evade regulation. We present a study aimed at determining whether such a case, the band this http URL, should be classified as politically right-leaning or as part of the general German rock genre. We sampled a German rock dataset and created a corpus for right-wing rock to use as reference in this analysis and found that we can confirm the intuitions from previous investigations that this http URL successfully maintains an ambiguity with regard to their political affiliation. However, the tendency is towards the right-wing spectrum. Lexical analyses reveal nationalistic narratives and two high-performing classifiers (up to 97% ROC-AUC score) label more than half of their songs as right-wing extremist. Our analysis provides insight into how computational methods can improve the process of identifying right-wing extremist tendencies in music, especially in borderline cases like this http URL. The code and data are made available for future research.

Computation and Language (cs.CL)

arXiv:2609.39460 [cs.CL]

(or arXiv:2609.39460v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.39460 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Text integral sub licența deschisă a publicației · 293 cuvinte

Subiecte conexe