The weaponisation of algorithmic bots in the music industry - market manipulation and policy recommendations

Abstract

This thesis investigates how malicious actors (automated architects) weaponise several types of bots to exploit vulnerabilities in music industry markets and harm relevant stakeholders. To conduct the analyses, this thesis focussed on three specific types of bots - Ticket Bots, Social Bots and Music Streaming Bots. These bots demonstrate how bots effectively manipulate online platforms’ environments to distort organic users’ and stakeholders’ perceptions and decision-making processes and erode trust in platform safeguarding mechanisms. The analysis of each chapter combined Richard Thaler’s ‘Choice Architecture Theory’ with Daniel Sussers’ ‘Online Manipulation Theory’. These frameworks demonstrated how bots achieve both overt and covert forms of manipulation, offering a new insight into their broader economic and social impact.

A central contribution of this thesis is the critical evaluation of existing UK legislation. Currently, UK legal responses to malicious bot activity are fragmented - courts use inconsistent approaches, and legislation lacks concise definitions of prohibited bot activities in the online environment. Through using a comparative jurisprudential analysis, the research identifies gaps in UK legislation and proposes targeted reforms. These include strengthening legislative terminology of the several types of bots, clarifying liabilities and imposing more responsibility and accountability on online platforms to develop more effective safeguards - addressing the identified market vulnerabilities.

The research further contributes by anticipating the trajectory of bot technologies, highlighting their integration with advanced AI technologies such as deepfakes and large language models. By mapping this trajectory, this thesis not only highlights the urgent need for UK policy reform but provides a foundation for future research on the manipulation of online environments using AI technologies and effective private and public regulatory responses.

Overall, the main contribution of this thesis is shedding light on an area that has been overlooked in the legal, technological and music field for too long. It provides actionable policy reformations, arguing that without proactive and targeted reform, bots will increasingly destabilise cross-sector markets and grant automated architects the ability to manipulate broader economic and societal values.

Thesis is embargoed until 31 July 2031.

Date of Award	Jul 2026
Original language	English
Awarding Institution	Queen's University Belfast
Supervisor	Giancarlo Frosio (Supervisor) & Hans Vandierendonck (Supervisor)