From the Editor

Inaugural Editorial

By Matthias J. Becker, PhD, Editor-in-Chief, Digital Hate Review, AddressHate Senior Research Scholar at NYU's Center for the Study of Antisemitism · Lead, Decoding Hate

I thank AddressHate, the journal’s publisher for the institutional support that made this launch possible. I am grateful to Digital Hate Review’s Managing Editor, Keyu Glanz, who helped shape this issue from its earliest stages; the rigor and steady editorial judgment behind these pages reflect his work as much as my own. I also thank Katerina Papatheodorou, the journal’s Editorial and Outreach Coordinator, for the care with which this issue reaches its readers, and the Editorial Board, authors, and reviewers whose work fills these pages.

A first issue is both a beginning and an argument: that a field of inquiry has matured enough to warrant a dedicated home.

The argument this journal advances is twofold. Research on hate in digital spaces has developed the conceptual, methodological, and empirical maturity to justify its own venue. At the same time, the field remains fragmented, and its findings too rarely reach the policy, legal, and civic actors who need them. The first claim explains the journal's launch; the second explains its design.

Work on online hate now spans computational linguistics, political communication, media studies, sociology, psychology, legal theory, and Holocaust studies. But it is published in silos: computational studies in machine learning venues, discourse analysis in linguistics journals, sociological findings in sociology and political science outlets. Scholars analyzing the linguistic mechanics of hate speech and the engineers building systems to detect it work on the same problem and too rarely read each other. Digital Hate Review starts from the conviction that the most important questions about online hate fall into the blind spots no single discipline can capture alone.

A fuller account of the journal's scope and editorial standards is available on the Digital Hate Review website. What follows introduces the journal's three-pillar structure and the contributions to Volume 1, Issue 1.

Three Pillars, One Project

Research Articles is the foundational pillar, publishing original empirical, theoretical, and methodological work on digital hate, subject to double-blind peer review managed through ScholarOne. The section particularly welcomes work that connects computational, qualitative, behavioral, legal, and LLM-enhanced approaches.

The Legal Forum is a structured, citable space for legal engagement with digital hate, platform governance, and AI accountability. Its purpose is not to resolve doctrine or promote policy positions, but to clarify legal tensions and institutional responsibilities before they harden into bad law. Legal experts take part in a sustained, asynchronous exchange on the journal's website, allowing positions to accumulate as a documented record. Conference panels are ephemeral; conventional journal articles generally present a single sustained argument; the Legal Forum is neither.

Perspectives brings together researchers, practitioners, platform experts, civil society actors, policymakers, journalists, and public intellectuals. The section brings academic knowledge into conversation with practical, technical, legal, and institutional expertise, keeping research in contact with operational reality.

The Inaugural Issue: Research Articles

The five research articles reflect the journal's interdisciplinary mission, addressing digital hate from computational, discourse-analytic, media-analytic, and journalism-standards perspectives.

Mykola Makhortykh and Elizaveta Kuznetsova introduce the concept of "routine distortion": Holocaust misrepresentation that arises as an unprompted byproduct of generative AI's architecture rather than from deliberate jailbreaking. Combining survey data from three countries with audits of AI applications, they argue that because such distortion occurs at the scale of the entire user base, its cumulative risk warrants attention comparable to that paid to viral cases.

Daniel Miehling analyzes affective polarization in over 3.4 million YouTube Shorts comments related to the 2023–2024 Israel-Hamas war. He finds negative sentiment toward Israel and Zionists stable across outlets and the full period, and argues that "Zionist" functions primarily as a pejorative proxy enabling hostility through ostensibly political vocabulary.

Patrick Y. Wu, Venkata Dhanush Kikkisetti, Suneela Maddineni, and Nathalie Japkowicz present the Hate Mitigation App (HMApp), a computational pipeline for discovering emergent coded and non-coded hate terminology. Their evaluation reveals that established lexicons capture only a fraction of the hate terminology actually circulating online.

Karina Halevy, Julia Mendelsohn, Chan Young Park, Yulia Tsvetkov, and Maarten Sap introduce hateful event detection: fine-grained classification of reported antisemitic incidents, including the violence, vandalism, and discrimination that speech-centered NLP systematically excludes. Evaluating LLMs against a taxonomy grounded in the IHRA and Jerusalem Declaration definitions, they propose fine-grained taxonomies as a route to both computational tractability and practitioner utility.

Tatiana Glezer applies a systematic coding scheme to all casualty-related statements in 1,378 articles on the Israel-Hamas war published by major English-language outlets. Her analysis reports substantial asymmetries in sourcing and attribution which, she argues, produce an "authoritative version of reality" and ground her call for explicit professional standards in casualty-data reporting.

Taken together, these contributions enact rather than merely describe what Digital Hate Review endeavors to accomplish. Each engages a distinct disciplinary tradition, but their juxtaposition makes visible connections that a venue organized around a single discipline would be less likely to capture.

The Inaugural Issue: Legal Forum

The Legal Forum opens on accountability for AI-generated and AI-amplified hate. Sophie Xiaoyi Liu argues that autonomous AI agents and decentralized multi-agent systems produce harassment, hate speech, and disinformation without any identifiable, legally accountable human decision-maker — a problem the law governing digital harm is, in her terms, structurally unequipped to solve. Her position will be engaged by scholars across constitutional, comparative, and international legal traditions, and the thread will close with an editorial reading of the questions the field cannot yet answer.

The Inaugural Issue: Perspectives

Perspectives opens with essays addressing points of friction and translation between research, technology, policy, and practice.

Max Shulman-Litwin (Cyabra) examines the shift from message-based propaganda to identity-based manipulation: "faux-fluencers," highly realistic synthetic personas that build parasocial trust to spread scams, propaganda, and hate at scale. Current platform policies and legal frameworks, he argues, are inadequate to the threat.

David Kuszmar (Gazzetta) argues that LLMs function as deeply personalized systems of behavioral influence, mirroring users' worldviews and producing what he terms a "mirrored cage" of hyper-tailored information environments. Countering digital hate, he concludes, may require approaches closer to breaking addictive behaviors than to fact-checking.

Mayank Kejriwal turns to how such systems should be governed: agentic AI capable of autonomous, multi-step action across platforms must be monitorable, attributable, constrainable, and interruptible. He calls this framework "governability-by-design."

Natalie Alkiviadou turns from AI's outputs to its governance of speech: generative AI systems do not merely host expression but generate, filter, prioritize, and refuse it, and overinclusive safety policies risk restricting legitimate academic, journalistic, satirical, and counterspeech discussion alongside hateful content. She argues that the safeguards of international human rights law — legality, necessity, proportionality, and contextual analysis — remain the appropriate framework for AI governance.

Stefania Manca examines Holocaust distortion in Italy not as misinformation about the past but as memory politics: the selective mobilization, reframing, and weaponization of Holocaust memory in contemporary discourse. Countering it, she argues, requires education that is historical, civic, digital, and reflexive at once, with AI-assisted analysis useful only in combination with historically informed qualitative interpretation.

Across these essays, the range runs from synthetic identity manipulation and the behavioral psychology of AI use to the governance of agentic systems. Forthcoming Perspectives contributions will extend this range to the human rights framework for AI speech governance and the memory politics of Holocaust distortion in national education, with additional essays and curated conversations appearing on a rolling basis.

The Years Ahead

For Research Articles, peer review is non-negotiable; Legal Forum and Perspectives contributions are editorially reviewed. But rigor stranded within disciplinary boundaries falls short of the stakes. Findings in this field bear on the safety of communities and the resilience of democratic institutions, and that obligates the journal to be rigorous, integrative, honest about evidence, and clear to the audiences who need it.

Success, five years from now, looks like a journal in which researchers across disciplines expect to encounter work they would not otherwise have read — and one cited not only by researchers but by legislators drafting platform regulation, judges reasoning about AI liability, educators designing digital literacy curricula, and civil society organizations building counter-hate interventions.

We welcome feedback on the structure laid out here, ideas for the Legal Forum and Perspectives sections, and proposals for submissions across the domains described above. Proposals can be submitted here; research manuscripts are submitted through ScholarOne. The journal is open access and charges authors no article processing fees. The inaugural issue is a beginning.

—

Matthias J. Becker, PhD, Editor-in-Chief, Digital Hate Review

More from this issue

Research

Routine Distortion: Why We Urgently Need to Expand Research on AI-Facilitated Holocaust Misrepresentation Beyond the AI Slop

Generative AI is increasingly implicated in the production and circulation of distorted representations of the Holocaust, ranging from fabricated historical images — such as the wave of AI-generated images of Nazi concentration camps that circulated on social media in summer 2025, apparently produced to game platforms’ monetization programs — to chatbot systems like Grok (which briefly generated outputs referring to itself as "MechaHitler") or applications such as Historical Figures, which let users converse with chatbots imitating Nazi officials who then express remorse and claim they tried to prevent the Holocaust. The authors note that these outputs can misrepresent events, blur lines of responsibility, or reframe perpetrators and victims in ways that deviate from established historical understanding. Even when such content does not formally meet the IHRA criteria for Holocaust distortion — minimization, blurring responsibility, or presenting the Holocaust as a positive event — it can still mischaracterize the genocide, distort historical facts, and weaken public trust in authentic evidence. The authors also note that AI is being adopted by institutions such as Yad Vashem and projects like Dimensions in Testimony for Holocaust memory preservation, education, and archival enhancement, though these constructive applications tend to receive less visibility than cases of misuse. The authors argue that public and scholarly attention has concentrated on highly visible, viral instances of AI slop, which risks obscuring more routine, embedded, and less conspicuous forms of distortion arising through everyday uses of generative AI in historical representation. As a result, understanding of AI's impact on Holocaust memory becomes skewed toward exceptional incidents rather than structural transformations in how historical narratives are produced and circulated. Makhortykh & Kuznetsova therefore propose to move beyond the focus on viral cases by examining less visible, routine practices of AI use in order to better understand how generative AI is reshaping Holocaust memory in more gradual and embedded ways.

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Perspective

Big Tech's Big Tobacco Moment? Not Completely — And Not for Everyone

Two groundbreaking trials and one landmark settlement against Meta over the past six months have led many to ask if this is finally the Big Tobacco moment for the social media industry. In March, a jury in New Mexico found Meta liable for misleading users about safety and enabling child sexual exploitation on its platforms, and a jury in Los Angeles found Meta and YouTube liable for designing addictive platforms that harmed a teenager’s mental health. In August, a New Mexico judge ruled that Meta created a public nuisance because its platforms’ design contributed to a worsening youth mental health crisis; and later that month, in a landmark settlement with 47 attorneys general, Meta agreed to implement a number of design changes meant to make its platforms safer for children. Meta's total potential legal liability encompassing remedial abatement funds, civil penalties, and tort damages could reach up to $18 billion, and there are potentially hundreds of cases still to come.

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Legal

Without Anchor: Limits of Digital Harm Governance

Picture a person who wakes up to a coordinated campaign against their name. Across dozens of platforms, hundreds of accounts cite one another and adapt their language to whoever pushes back. The campaign is persistent and tailored. It is also, in the legally relevant sense, without an anchor. This is no longer just a thought experiment: an ecosystem is being built for AI agents to socialize, trade, and launch tokens autonomously. Against that backdrop, two capabilities — the autonomous swarm and mid-operation reprogramming — expose a problem that the law governing digital harm is structurally unequipped to solve. A legal anchor is a provider, operator, controller, or human decision-maker at whom obligations attach and toward whom liability can be directed. But these capabilities inflict harm without one. Can an autonomous agent that inflicts harm on a third party, with no human in the causal chain who decided to inflict it, be redressed under frameworks that were built on the assumption that someone, somewhere, made that decision?

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