arXiv subjects

Alex Leitch

Publications and source records attributed to Alex Leitch.

8 recordsLinked to original sources

arXiv2026

Red Flags and Cherry Picking: Reading The Scientific Blackpill Wiki

Incels are an online community of men who share a belief in extreme misogyny, the glorification of violence, and biological essentialism. They refer to their core ideology as "The Blackpill", a belief that physical attraction is the only path to romantic success and that women are only attracted to one very specific, hypermasculine archetype. This is not only a belief system; incels believe their ideology grounded in hard science. The research that incels use as evidence of their belief system is collected in an extensive online document, the Scientific Blackpill wiki page. In this research, we analyze the claims made on the wiki against the research cited to assess how the wiki authors are using or misusing science in support of their ideology. We find that the page largely cites legitimate science and describes it partly or mostly accurately. However, in discussing it, the results are often overgeneralized, stripped of context, or otherwise distorted to support the preexisting incel viewpoint. This echoes previous findings about motivated reasoning and borrowing scientific legitimacy in other misinformation and conspiracy-minded ideologies. We discuss the implications this has for understanding online radicalization and information quality.

cs.HC↗

arXiv2026

In Bad Faith: Assessing Discussion Quality on Social Media

The quality of a user's social media experience is determined both by the content they see and by the quality of the conversation and interaction around it. In this paper, we look at replies to tweets from mainstream media outlets and official government agencies and assess if they are good faith, engaging honestly and constructively with the original post, or bad faith, attacking the author or derailing the conversation. We assess automated approaches that may help in making this determination and then show that within our dataset of replies to mainstream media outlets and government agencies, bad faith interactions constitute 68.3% of all replies we studied, suggesting potential concerns about the quality of discourse in these specific conversational contexts. This is particularly true from verified accounts, where 91.7% of replies were bad faith. Given that verified accounts are algorithmically amplified, we discuss the implications of our work for understanding the user experience on social media.

cs.SI↗

arXiv2026

"Why I Took the Blackpill": A Thematic Analysis of the Radicalization Process in Incel Communities

Incels, or "involuntary celibates", are an extreme, misogynistic hate group that exists entirely online. Members of the community have been linked to acts of offline violence, including mass shootings. Previous research has engaged with the ideologies and beliefs of incels, but none has looked specifically at the radicalization process. In this paper, we perform a thematic analysis on social media posts where incels describe their own radicalization process. We identified six major themes grouped into four chronological steps: Pre-radicalization (themes of Appearance, Social Isolation, and Psychological issues), Searching for Blame, Radicalization, and Post Radicalization. These results align closely with existing work on radicalization among other extremist groups, bringing incel radicalization inline with a growing body of research on understanding and managing radicalization.

cs.SI↗

arXiv2025

Unlimited Editions: Documenting Human Style in AI Art Generation

As AI art generation becomes increasingly sophisticated, HCI research has focused primarily on questions of detection, authenticity, and automation. This paper argues that such approaches fundamentally misunderstand how artistic value emerges from the concerns that drive human image production. Through examination of historical precedents, we demonstrate that artistic style is not only visual appearance but the resolution of creative struggle, as artists wrestle with influence and technical constraints to develop unique ways of seeing. Current AI systems flatten these human choices into reproducible patterns without preserving their provenance. We propose that HCI's role lies not only in perfecting visual output, but in developing means to document the origins and evolution of artistic style as it appears within generated visual traces. This reframing suggests new technical directions for HCI research in generative AI, focused on automatic documentation of stylistic lineage and creative choice rather than simple reproduction of aesthetic effects.

cs.HC↗

arXiv2025

Cross-Platform Violence Detection on Social Media: A Dataset and Analysis

Violent threats remain a significant problem across social media platforms. Useful, high-quality data facilitates research into the understanding and detection of malicious content, including violence. In this paper, we introduce a cross-platform dataset of 30,000 posts hand-coded for violent threats and sub-types of violence, including political and sexual violence. To evaluate the signal present in this dataset, we perform a machine learning analysis with an existing dataset of violent comments from YouTube. We find that, despite originating from different platforms and using different coding criteria, we achieve high classification accuracy both by training on one dataset and testing on the other, and in a merged dataset condition. These results have implications for content-classification strategies and for understanding violent content across social media.

cs.CL↗

arXiv2025

Evaluating Machine Expertise: How Graduate Students Develop Frameworks for Assessing GenAI Content

This paper examines how graduate students develop frameworks for evaluating machine-generated expertise in web-based interactions with large language models (LLMs). Through a qualitative study combining surveys, LLM interaction transcripts, and in-depth interviews with 14 graduate students, we identify patterns in how these emerging professionals assess and engage with AI-generated content. Our findings reveal that students construct evaluation frameworks shaped by three main factors: professional identity, verification capabilities, and system navigation experience. Rather than uniformly accepting or rejecting LLM outputs, students protect domains central to their professional identities while delegating others--with managers preserving conceptual work, designers safeguarding creative processes, and programmers maintaining control over core technical expertise. These evaluation frameworks are further influenced by students' ability to verify different types of content and their experience navigating complex systems. This research contributes to web science by highlighting emerging human-genAI interaction patterns and suggesting how platforms might better support users in developing effective frameworks for evaluating machine-generated expertise signals in AI-mediated web environments.

cs.HC↗

arXiv2024

Ephemeral Myographic Motion: Repurposing the Myo Armband to Control Disposable Pneumatic Sculptures

This paper details the development of an interactive sculpture built from deprecated hardware technology and intentionally decomposable, transient materials. We detail a case study of "Strain" - an emotive prototype that reclaims two orphaned digital artifacts to power a kinetic sculpture made of common disposable objects. We use the Myo, an abandoned myoelectric armband, in concert with the Programmable Air, a soft-robotics prototyping project, to manipulate a pneumatic bladder array constructed from condoms, bamboo skewers, and a small library of 3D printed PLA plastic connectors designed to work with these generic parts. The resulting sculpture achieves surprisingly organic actuation. The goal of this project is to produce several reusable components: software to resuscitate the Myo Armband, homeostasis software for the Programmable Air or equivalent pneumatic projects, and a library of easily-printed parts that will work with generic bamboo disposables for sculptural prototyping. This project works to develop usable, repeatable engineering by applying it to a slightly whimsical object that promotes a strong emotional response in its audience. Through this, we transform the disposable into the sustainable. In this paper, we reflect on project-based insights into rescuing and revitalizing abandoned consumer electronics for future works.

cs.HC↗

arXiv2024

LLMs as Academic Reading Companions: Extending HCI Through Synthetic Personae

This position paper argues that large language models (LLMs) constitute promising yet underutilized academic reading companions capable of enhancing learning. We detail an exploratory study examining Claude from Anthropic, an LLM-based interactive assistant that helps students comprehend complex qualitative literature content. The study compares quantitative survey data and qualitative interviews assessing outcomes between a control group and an experimental group leveraging Claude over a semester across two graduate courses. Initial findings demonstrate tangible improvements in reading comprehension and engagement among participants using the AI agent versus unsupported independent study. However, there is potential for overreliance and ethical considerations that warrant continued investigation. By documenting an early integration of an LLM reading companion into an educational context, this work contributes pragmatic insights to guide development of synthetic personae supporting learning. Broader impacts compel policy and industry actions to uphold responsible design in order to maximize benefits of AI integration while prioritizing student wellbeing.

cs.HC↗