Editors Note: This piece is the practical, step-by-step follow-up to my last article, Your Face Is No Longer Yours (And Meta Doesn’t Care). While that article explained why and how tech platforms fail us, this playbook is all about action. Below, you will find concrete tools, survivor-led tactics, and alternative security steps to protect human rights defenders, journalists, and everyday citizens when big tech monopolies choose to look away.

The most dangerous thing about a deepfake is not always that people believe it. Sometimes the damage is already done before anyone figures out it is fake.

A manipulated video can travel across Instagram, Facebook, WhatsApp, X, TikTok and private group chats in hours. It can be downloaded and copied instantly, reuploaded across accounts, burner profiles, stripped of its original context, and weaponized into targeted harassment, impersonation, sexual violence, political disinformation or reputational assault. It hijacks a target’s likeness to inflict severe psychological and real-world harm before they even know it exists. And once the weaponized content enters algorithmic circulation, the target is often left alone to clean up the wreckage.

That is one of the clearest lessons from recent Meta Oversight Board cases: platform safety architectures are still fundamentally reactive, highly fragmented, and structurally designed to shift the burden of proof and policing onto the victim. Last week, I provided a full diagnostic autopsy of this structural failure, mapping its fallout across two women from entirely different worlds.

We saw Dorothy McHugh, a 77-year-old Scottish local councillor, whose likeness was hijacked by a deepfake video ahead of an election. Meta hid behind a legacy “public figure” loophole, allowing the video to circulate for ten months while automated systems blocked her from reaching a human reviewer.

Alongside her stood a young Muslim health advocate in Europe whose television interview was altered by generative AI into a series of humiliating videos. Meta’s algorithms summarily rejected her reports because of a hyper-narrow policy gap: since the video fabricated her conduct rather than altering her physical anatomy, the platform ruled it did not count as a violation.

When tech giants apply these rigid, checklist-driven policies to complex human realities, they create dangerous gray areas that bad actors systematically exploit. And the human toll is immediate: severe character defamation, targeted xenophobic and misogynistic harassment, and prolonged psychological re-traumatization.

In this playbook, we pivot from diagnosis to design: what should you actually do if this happens to you, a colleague, or a community you are defending?

1. Preserve First. Report Second.

Before reporting a harmful deepfake, document and preserve evidence first, then report. This may feel counterintuitive. When confronted with a digital attack, our immediate visceral instinct is to “get this down immediately” and hit that report button. This is a trap. In the rush to erase the harm, users often delete the very proof required to stop it. Posts disappear, accounts get suspended, captions change, and copies move elsewhere. Once content is scrubbed by the platform, the evidence you need for an appeal, legal recourse, journalism, or advocacy vanishes with it.

Before you touch a platform’s reporting forms, you must document the pattern. Capture transient information that is at risk of being moved, altered, or lost completely.

• Record raw video screen recordings and capture screenshots of the deepfake playing in real time, capturing how it renders on screen.

• Log the exact account names and handles, and copy the full URLs of the source profiles.

• Document the temporal context: record the precise date, time, and timezone of your capture.

• Capture the surrounding engagement and context: document captions, comment sections, reposts, trackbacks, and visible engagement metrics.

If the content is spreading across multiple accounts or platforms, track them in a central place too. Document the pattern (coordinated ecosystem) rather than treating each upload as an isolated incident.

Tools & Resources

• Hunchly (Desktop Software): A professional-grade digital investigation tool that runs silently in your browser background. It automatically records, logs, and timestamps every URL, webpage, and image you visit, creating an unalterable history built to serve as valid legal evidence.

• Internet Archive’s Way Back Machine or Archive.today (Web Tool): A free, instant way to take a permanent text and graphic snapshot of a specific URL. Even if the perpetrator deletes the post or gets suspended, the archived snapshot remains public and unchangeable.

• Starling Lab for Data Integrity: A highly innovative project by Stanford and USC utilizing decentralized web protocols and cryptographic hashing to create immutable, tamper-proof ledgers of visual evidence, ensuring digital chains of custody that withstand corporate deletion.

• OSINT Framework: The primary web-based directory that organizes open-source intelligence tools into a structured, browsable tree. It is maintained by the OSINT community to pivot through data categories (usernames, emails, maps, etc.) without relying on commercial software dashboards.

2. Report the Underlying Violation (the Harm), Not the Technology

This is where people lose critical time. A deepfake is a mechanism; the specific abuse it produces it executes is the actual policy infraction and violation.

One of the biggest structural mistakes of tech platforms’ trust and safety teams is their obsession with authenticity over intent—treating synthetic media as a technical box to check. But the critical question is never, “Is this file fake?” It is “What is this fake being weaponized to achieve?”

If someone uses a manipulated video to humiliate a woman, impersonate a public figure, spread hate, distribute non-consensual sexual content, or incite harassment, report the underlying policy violation rather than generic AI labels. Report it as:

• Harassment, stalking, or bullying

• Wholesale impersonation

• Hate speech or incitement to violence

• Non-consensual intimate imagery (NCII) or sextortion

• Deception, fraud, or identity theft

Tools & Resources

• Take It Down (by NCMEC) (Under 18): A free, anonymous tool operated by the National Center for Missing & Exploited Children explicitly designed to stop the online spread of non-consensual explicit images or deepfakes of individuals under 18.

• StopNCII.org (for adults, global coverage): The gold standard for intimate deepfake removal worldwide. Operated by the Revenge Porn Helpline in partnership with a global council of international NGOs, this platform uses secure, on-device hashing technology. The multi-language interface allows global victims to generate security hashes to stop sharing across networks (including Meta) without their media files ever leaving their devices.

• Chayn: A phenomenal, independent survivor-led global majority movement that builds open-source, multilingual digital safety resources and trauma-informed reporting pathways for gender-based violence, completely outside corporate templates.

• Platform Direct Reporting: Skip generic “AI” forms and automated generic feedback loops. Use Meta’s direct dedicated reporting channels for Harassment/Bullying, Impersonation (Facebook Form or Instagram and Threads), or Hate Speech, or sextortion, to trigger stricter policy enforcement and a more stringent review.

3. Record and Appeal Every Automated Rejection

Never assume that a rejected report means the content complies with platform and community guidelines. Automated moderation systems handle the vast majority of first-line platform triage, and they routinely mistake and misread context, subtext, and localized language.

If the platform gives you an option to appeal, use it immediately. Keep a meticulous log of the corporate response: screenshot your original report submission, the automated rejection notification, and the subsequent appeal confirmation.

This matters because while your single failed report is a frustrating administrative hurdle, it can also become evidence of a broader systemic enforcement failure, especially if multiple people report the same content and Meta repeatedly declines to act (part of a logged trail). And this can be be escalated to regulatory authorities.

Tools & Resources

• Oversight Board Appeals Portal: If you exhaust Meta’s internal appeal options and severe, high-stakes content remains online, check your eligibility to submit your case directly to the independent Oversight Board for binding evaluation.

• Digital Rights Foundation (DRF) Cyber Harassment Helpline: A pioneering grassroots initiative in South Asia that offers specialized support tracking, documenting, and contesting automated platform rejections for regional language users facing weaponized online harassment.

• Moderation Evidentiary Tracker (Template): Create and maintain a simple spreadsheet logging: Platform Reference ID #, Source URL, Date Reported, Initial Automated Decision, Date Appealed, and Final Enforcement Outcome. Attach timestamped screenshots to keep your paper trail intact.’

4. Don’t Accidentally Make the Deepfake More Viral.

Say it with me: debunking should not become amplification.

This is a common trap and one of the hardest psychological parts of responding to manipulated media. When targeted by a malicious campaign, people understandably want to publicly expose the lie. However, quoting, embedding, or reposting the full original deepfake video—even to condemn it—feeds the platform’s algorithms recommendation engines, distributes the media to new audiences, and scales the original harm.

The objective is to provide enough baseline context to to explain the abuse (neutralize the deception) without becoming another free distribution channel for the perpetrator. Implement defensive communication tactics. Consider using:

• Utilize static, flat screenshots rather than moving video files.

• Apply heavy pixelation, crops, or blurs to sensitive visual elements.

• Isolate short, specific audio/visual fragments rather than whole files.

• Superimpose aggressive text watermarks directly over the graphic.

• Rely on precise, purely text-based descriptions of the manipulation.

Tools & Resources

• Redacted App (or Signal Media Editor): Free tools to quickly blur faces, crop out identifying details, or place heavy text watermarks (e.g., “MUTILATED/ DECEPTIVE MEDIA”) across a screenshot before sharing it for awareness.

• Canva (Text Overlay): If you must share a frame to debunk it, use Canva or similar editing tool, to slap a bright, unmissable banner over the image so it can never be screenshotted and reused maliciously out of context.

• WITNESS "Prepare, Don't Amplify" Guide: An invaluable methodology developed by my team at the global human rights organization WITNESS, showing grassroots advocates how to expose synthetic deception safely without inadvertently triggering algorithm-driven viral loops.

5. Play Whack-a-Mole Strategically

Deepfake harm rarely stays confined to a single upload. Once a video begins circulating, people can download it, crop and re-edit it, add new captions, change the audio or cross-post it to entirely different platforms and accounts. Removing the initial post often does very little to stop the momentum. To track copies, you must search laterally:

• Monitor highly distinctive phrasing, syntax patterns, or specific typos from the original caption.

• Track the accounts and network profiles driving high engagement volumes in the original comment sections.

• Audit variants of the subject’s name across secondary platforms and alternative networks.

• Maintain a centralized tracking log of new instances, duplicates, noting when they appeared and which accounts are posting them and driving the engagement.

This is an area where platforms must do far more. Once a piece of manipulated media is determined to violate platform rules, the target should not have to spend weeks chasing down identical variations, playing whack-a-mole with hundreds of copies.

Tools & Resources

• Google Reverse Image Search & TinEye: Upload a clean screenshot or still frame from the deepfake to run a reverse-image lookup, tracing where else the file or its direct visual variations have been hosted across the web.

• Google Alerts & Talkwalker: Set up real-time keyword alerts for the specific phrase, hashtag, or target victim’s name used in the deepfake caption to catch new uploads instantly.

• Bellingcat Digital Toolkit: A community-driven, public-interest collection of open-source methodology tools designed by independent researchers to trace media footprints, cross-reference metadata, and map coordinated distribution networks without corporate assistance.

6. Escalate Outside the Corporate Ecosystem

Meta and Silicon Valley executives cannot be the ultimate arbiters of human safety. Depending on the situation and jurisdiction, a weaponized deepfake routinely crosses the threshold into explicit criminal or civil violations, including stalking, extortion, character defamation, identity theft, fraud, civil rights violations, and coordinated election interference.

When an attack escalates and the harm becomes more serious, look past corporate chat bots and broken platform reporting forms. Connect early with journalists legal counsel, independent digital rights organizations and coalitions, civil society groups, investigative journalists, and relevant regional regulatory watchdogs. A glitchy or unresponsive platform reporting form or chatbot is never your only avenue of recourse.

Tools & Resources

• Cyber Civil Rights Initiative (CCRI): Offers a 24/7 crisis helpline (1-866-411-5237) providing legal resources, safety planning, and emotional support for victims of non-consensual intimate imagery.

• Local Cybercrime Reporting: File a formal report with federal cybercrime divisions (like the FBI’s IC3 in the US, or your regional equivalent) to build a legal paper trail. Here is a list of cybercrime agencies by country.

• European Digital Rights (EDRi) & Electronic Frontier Foundation (EFF): Powerful, independent civil-society networks in Europe and the US that bypass corporate channels to monitor structural policy failures, leverage regulatory frameworks (like the EU’s Digital Services Act), and advocate for systemic, non-corporate platform accountability.

• Access Now Digital Security Helpline: A global non-profit rapid-response emergency helpline offering 24/7 digital security and legal support in 9 languages (including Arabic, Spanish, French, Portuguese, Russian, Tagalog, Ukrainian, and Chinese) to help secure accounts, mitigate active digital attacks, and bypass broken algorithmic forms.

• Digital Rights Networks: Best for region-specific legal and localized civil society escalations. In regions where English-centric reporting forms fail, look to localized digital defense groups (like Luminate and Global Voices , Hiperderecho and TEDIC in Latin America, SMEX (Social Media Exchange) in the Arabic-speaking region, 7amleh the Arab Center for Social Media Advancement (focus on Palestine and Israel), or Digital Rights Foundation in South Asia) that maintain direct, high-priority escalation channels with Meta.

7. Journalists: Verify the Process, Don’t Just Declare the Result

Newsrooms carry an acute ethical and public responsibility. A manipulated asset does not become responsible reporting simply because a headline asserts that it is fake. Before embedding, linking to, or broadcasting deceptive media, journalists must evaluate whether exposing the material is fundamentally required to serve the public interest.

Rigorous journalistic verification demands identifying the earliest known upload node, auditing whether the audio track and visual layers originated together, forensically reverse-searching individual keyframes, testing for physical or lighting anomalies, and directly contacting the person depicted.

When digital manipulation itself becomes the news event, expose the forensic workflow—how you know it is false. Institutional trust is built and strengthened by showing your verification methodology and process, not simply by stating your conclusion.

Tools & Resources

• InVID / WeVerify Verification Plugin: The global standard tool used by the International Fact-Checking Network (IFCN) . This essential browser extension allows journalists to perform reverse image searches on video frames, analyze metadata, and parse localized contexts or regional video formats across cross-platform chats like WhatsApp and Telegram.

• Amnesty International YouTube Data Viewer: Paste any YouTube URL to extract hidden upload times and track down the original, earliest version of a piece of video evidence.

• Meedan (Check Platform): An innovative tech non-profit building open-source, multilingual, and highly collaborative workflows for global newsrooms and fact-checking collectives to verify media and track narrative warfare outside Western markets.

8. Pressure Platforms to Stop Making Victims Police the Network

Ultimately, none of these tips and survival strategies should obscure the structural reality: individuals and organizations targeted by synthetic abuse should not be responsible for discovering every copy, deciphering opaque corporate policy frameworks, filing repetitive forms, and persuading a trillion-dollar technology company to protect human life, and that the harm being experienced deserves human review. Platforms can, and must, intervene earlier.

True intervention must occur upstream. Platforms possess the technical capacity, and must be pressured, to identify violating content at the point of ingest, preventing near-identical copies from spreading. They must prioritize reports involving synthetic impersonation, non-consensual manipulation, and coordinated harassment. They must route high-risk cases to qualified human reviewers instead of closing support tickets automatically. Crucially, reporting systems must be designed around the operational reality that deepfake abuse is often a coordinated campaign, not an isolated post. That distinction matters.

And it must impose stronger penalties on repeat distributors.

Tools & Resources

• The Sovereign Tech Fund & Prototype Fund: Independent, public-interest funding bodies that finance decentralized, community-driven alternative technologies, open-source protocols, and privacy infrastructure to reduce global civil society’s reliance on corporate monopolies.

• AlgorithmWatch & European Center for Not-for-Profit Law (ECNL): Independent watchdog institutions leveraging public accountability mechanisms—like the EU Digital Services Act (DSA) and the AI Act—to legally pressure tech companies to audit their algorithmic recommendation engines and halt the monetization of coordinated harm.

• Civil Society Coalitions: Join and support campaigns led by digital transparency organizations like the Global Tech Justice Coalition or Mozilla Foundation that coordinate open letters, policy advocacy, and shareholder pressure targeting safety accountability at Meta.

We have spent years discussing deepfakes as though the central danger were that people might mistake something fake for something real. Unfortunately, that is only part of the problem. It is the wrong way to look at it, and definitely the wrong way to address it. It is a framing we were fed, and it is a deeply misleading one.

A deepfake causes enormous harm even when everyone eventually learns it is fake. The humiliation happened. The harassment happened. The lies circulated. The screenshots and search results remain indexed for the world to access today, tomorrow, and decades from now. Long after a public retraction is issued, the target is still forced to defend their human dignity against actions they never took, words they never uttered, and content to which they never consented.

Which is why our response cannot stop at labeling manipulated media. A digital sticker is a corporate smoke screen. The real policy question is not simply whether Meta can tell us that something is fake; it is whether platforms can intervene before deception becomes distribution, distribution becomes harassment, and harassment becomes irreversible real-world harm.

This narrow, technical obsession with authenticity rather than systemic harm isn’t new. We have seen this exact structural failure before in other catastrophic platform crises. And this isn’t a theoretical critique; it is an operational reality I have spent nearly two decades navigating on the front lines around the world.

Throughout my career leading global crisis response, documentation, and verification initiatives, I have worked directly alongside multilateral institutions, informal networks, and an incredible ecosystem of global majority and global north practitioners, advocates, and innovators. Together, we have built the workflows, toolkits, policies, and defensive strategies needed when tech platforms and regulatory actors choose to look away. Many of the operational methodologies and tactical resources I have detailed here—and continue to analyze—are shared directly on this Unembedded Substack platform to build our collective security.

What this global network has proven is that digital violence is defined by a dangerous convergence phenomenon. Modern media manipulation does not exist in a silo. We are witnessing the fusion of identity theft, gender-based violence, localized information warfare, and algorithmic amplification. This convergence creates unprecedented risk regulation challenges; it moves too fast for traditional, localized legal systems, and slips directly through the fragmented corporate policy departments of Silicon Valley.

Yet, within this convergence lies an opportunity for true safety and security. By shifting away from isolated, siloed reactions—where platforms only address a crisis when it impacts Western markets while ignoring what happens elsewhere—we can build cross-border, systemic advocacy. The technical mechanism of automated apathy that allows a deepfake to target a local councillor in the UK is the exact same architecture that leaves human rights defenders in active conflict zones completely exposed, and killed in masses by tech supported and driven systems like Israel’s Lavender system. The infrastructure is identical; the only difference is the extension and severity of the real-world consequences.

Those who suffer first, and the most, are always the most marginalized communities—women, religious minorities, migrants, and independent journalists operating under hostile regimes and even in our very own so-called “democratic” states. But this lawlessness is catching up with us all. A system that automates indifference in one region will inevitably deploy that same indifference against you. And it already is.

Until tech platforms design their systems around preventing rapid distribution and protecting human safety rather than merely labeling data, we are all left to fend for ourselves. This is why we must master how to preserve evidence, report strategically, limit amplification, and escalate when corporate channels collapse.

But let us be clear: those are survival tools. They are tactical stopgaps. They are not a substitute for true platform accountability, policy, and structural change.

Let’s Build Your Defense Strategy

Operating in modern media systems means facing rapidly shifting technological risks, information warfare, and institutional vulnerabilities.

If your organization, media team, board, or leadership circle needs specialized guidance to adapt to emerging online harms, navigate digital evidence, mitigate deepfake threats, or implement rigorous international information integrity strategies, let’s talk. Learn more about my practice, training programs, and bespoke advisory services or schedule a direct consultation at Raja Althaibani Strategic Advisory or email me directly at inquiries@rajaalthaibani.com

MASTER RESOURCE DIRECTORY

• If you need to remove intimate images/deepfakes: StopNCII.org (Global Adults) | Take It Down (Under 18) | Chayn (Multilingual Survivor Support).

• If you need 24/7 localized crisis escalation or security support: Access Now Helpline (24/7 in 9 languages) | SMEX (MENA Region) | 7amleh the Arab Center for Social Media Advancement (focus on Palestine and Israel) | Digital Rights Foundation (South Asia) | Hiperderecho (Latin America).

• If you need independent metadata verification & investigative archives: InVID / WeVerify Plugin | Meedan Check | Bellingcat Toolkit | Starling Lab.

• If you need legal advocacy, rights defense, & policy intervention: Cyber Civil Rights Initiative (CCRI) | EDRi (European Digital Rights) | EFF (Electronic Frontier Foundation) | AlgorithmWatch.

This is a non-exhaustive list.

About the Author

Raja Althaibani works at the intersection of media, harm, technology, and accountability—advising, training, investigating, and building infrastructure for practitioners navigating an information landscape that moves faster than most frameworks can follow. Her background spans human rights, journalism, international law, and open-source digital documentation.

She writes Unembedded—long-form analysis, reported essays, and field frameworks on media, power, harm, and who controls the story. It includes two ongoing series: The Safari Is Over, on how media covers harm and what better practice looks like, and The Field Dispatch, the intelligence arm of The Field—a community of practice she founded.

Work with Raja: inquiries@rajaalthaibani.com · contact form · www.rajaalthaibani.com · Linkedin

Are you worried about what your children, students, friends, or community are being exposed to online right now?

The teenage gunmen who carried out Monday’s deadly attack at the Islamic Center of San Diego did not radicalize in a vacuum.

They were shaped by systems, and manufactured by design.

While communities mourn the lives of Amin Abdullah, Mansour Kaziha, and Nadir Awad, commentators keep asking:

How does this keep happening?

The urgent question is:

How do we expect to protect young people from online radicalization while ignoring the algorithmic systems, dehumanizing political language, grievance economies, and engagement-driven infrastructures that normalize extremism in the first place?

The infrastructure of modern violence has fundamentally changed.

What once lived in fragmented corners of the internet is now embedded into everyday digital life, reaching children earlier, faster, and more intimately than ever before.

It connects seemingly disparate horrors: ISIS propaganda networks, the Christchurch mosque livestream, antisemitic synagogue attacks, and the rising global surge of femicide and targeted misogyny.

For years, Western institutions treated these threats as distant, fringe, or external. Domestic extremism was minimized, selectively labeled, or politically compartmentalized while the underlying systems continued expanding in plain sight.

Today, state actors, influencers, extremist networks, and platform economies increasingly exploit the same vulnerabilities: fear, isolation, humiliation, identity crises, discrimination, and social alienation.

The pipeline is digital, and its consequences are physical.

So I created this tip sheet not as a panic document, but as a practical starting point for parents, educators, journalists, organizers, and communities trying to understand what is actually happening around them, and what warning signs we can no longer afford to ignore.

This is only the beginning.

In the coming weeks, Unembedded will continue publishing:

• practical prevention guidance

• platform accountability analysis

• newsroom reporting frameworks

• policy pressure points

• school and community intervention strategies

• investigations into the systems shaping modern online radicalization

Prevention starts long before violence. It starts with understanding the systems shaping attention, identity, belonging, and belief.

Subscribe to Unembedded, and restock and share this with your networks.

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Please note: the guidance and frameworks shared through Unembedded will continue evolving as technologies, platforms, policies, and online behaviors rapidly change. Stay subscribed for updated analysis, corrections, resources, and future action frameworks.

— Raja Althaibani, Editor, Unembedded

About the Author

Raja Althaibani works at the intersection of media, harm, technology, and accountability—advising, training, investigating, and building infrastructure for practitioners navigating an information landscape that moves faster than most frameworks can follow. Her background spans human rights, journalism, international law, and open-source digital documentation.

She writes Unembedded—long-form analysis, reported essays, and field frameworks on media, power, harm, and who controls the story. It includes two ongoing series: The Safari Is Over, on how media covers harm and what better practice looks like, and The Field Dispatch, the intelligence arm of The Field—a community of practice she founded.

Work with Raja: inquiries@rajaalthaibani.com · contact form · www.rajaalthaibani.com · Linkedin

About the Author

Raja Althaibani works at the intersection of media, harm, technology, and accountability—advising, training, investigating, and building infrastructure for practitioners navigating an information landscape that moves faster than most frameworks can follow. Her background spans human rights, journalism, international law, and open-source digital documentation.

She writes Unembedded—long-form analysis, reported essays, and field frameworks on media, power, harm, and who controls the story. It includes two ongoing series: The Safari Is Over, on how media covers harm and what better practice looks like, and The Field Dispatch, the intelligence arm of The Field—a community of practice she founded.

Work with Raja: inquiries@rajaalthaibani.com · contact form · www.rajaalthaibani.com · Linkedin

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Part 1 covered the first three shifts media practitioners should make before reporting— pitch the system, report the consequence, center the burden-bearers. Here are two more bonus shifts to carry with you. Because I care, and because I want us to win.

From Killing Spectacle: 15 Shifts for Reporting on Online Harm and Extremism, a guide for journalists, editors, producers, researchers, and media practitioners. Published here in parts. Each installment stands alone. The full picture builds across the series.

Start here: Part 1: Frame the Story Right .

Here are two more shifts to make in our daily practice to help us kill the ‘spectacle’ in ‘spectacle journalism’.

My first piece published here covered first three mindset and technical shifts, before reporting: pitch the system not the spectacle, report consequence not conflict, center the burden-bearers not the perpetrators. Those shifts are about what story you’re telling and whose experience is at the center of it.

These two are about something that happens before any of that, reading the information environment you’re working inside before you let it assign the story for you.

On beats covering online harm, extremism, and AI abuse, the platform is not a neutral surface. It is an active editorial force. It decides what looks significant. It manufactures the appearance of consensus. It makes fringe content look mainstream and widespread harm look marginal. Journalists who don’t account for that are not reporting reality. They are reporting the platform’s version of reality, which is designed, in specific and documented ways, to serve interests other than public understanding.

These two shifts are about closing that gap before the first word is written, or first raw video is collected, edited, or clipped.

Shift 4: Virality is evidence of distribution, not importance

Unlearn: Treat trending content as proof that something matters.

Relearn: Virality tells you something was distributed at scale. It tells you almost nothing about whether it reflects reality.

One of the most corrosive habits in covering online harm and extremism is treating visibility as proof. A piece of content goes viral. It appears in your feed, your editor’s feed, your source’s feed. It feels significant because it is everywhere.

But everywhere on a platform is an editorial decision made by an algorithm, not a measure of cultural reality, social consensus, or genuine threat. Platforms are built to surface conflict and blur the line between significance and visibility. Journalism walks straight into that trap when it treats the trending tab as an assignment editor.

Urgency and importance are not the same thing. A piece of content can reach ten million people and reflect almost nothing about how those people actually think, behave, or live. A pattern that affects millions can be entirely invisible on a platform because it doesn’t produce the engagement mechanics that make content travel.

The shift is learning to ask:

is this visible because it is significant, or does it seem significant because it is visible?

What this looks like in practice

The 2024 tradwife surge looked, from inside the feed, like a mass cultural shift: a generation of women returning to domestic roles. Mainstream coverage treated it that way. Research from Monash University and the International Journal of Communication found no evidence of that in behavioral data. What the data showed was that recommendation algorithms were artificially funneling users toward increasingly extreme gender content. The trend didn’t reflect what women wanted. It reflected what the platform rewarded and amplified. Reporting it as a cultural shift normalized extremist content through perceived popularity, exactly the outcome the amplification was designed to produce.

The same failure appears constantly on extremism beats. Coordinated seeding makes fringe content look mainstream. Manufactured outrage cycles make marginal figures look culturally significant. The platform’s engagement mechanics are not neutral. They are specifically designed to surface the most inflammatory version of any story. Treating that surface as reality is a reporting failure, not just an editorial one.

Editorial test:

If this were not trending, would you still assign it?

If the answer is no, you are covering distribution, not reality.

If this incident had never been filmed, clipped, or algorithmically amplified, would it still matter?

If the answer is yes, that is where the story begins.

Field note on extremism and online harm beats specifically:

On these beats the virality problem is often deliberate, not incidental. Bad actors engineer viral moments specifically to manufacture the appearance of consensus, to make a fringe position look mainstream, a marginal figure look culturally dominant, an isolated incident look like a pattern. The tradwife surge was organic platform mechanics producing a distorted picture. Coordinated extremist content seeding is the same distortion produced intentionally.

The verification question is the same in both cases:

is this visible because it is significant, or significant because it is visible?

Before escalating any trending story on these beats, ask whether the spike is organic or cluster-driven. The answer changes what you’re actually covering.

Toolkit 4: Auditing virality before you escalate

Before escalating any trending story, run this test:

Does this affect policy, safety, public resources, or a meaningful number of people beyond the feed?

If not, you are covering distribution.

For checking whether a spike is organic or coordinated: Junkipedia tracks coordinated inauthentic behavior and platform manipulation; the Stanford Internet Observatory publishes platform-specific research on amplification mechanics; CrowdTangle (now Meta Content Library) and Brandwatch track cross-platform spread patterns.

For situating platform trends in behavioral reality: look for data that exists outside the platform such as surveys, behavioral research, policy data, academic studies that either corroborates or contradicts what the platform surface suggests. Monash University’s platform research and the Reuters Institute’s Digital News Report are both useful starting points for cross-referencing platform visibility against real-world data. Also check out Bellingcat’s Online Investigation Toolkit.

Newsworthiness test before escalating any trend:

does this have policy effects, safety implications, measurable behavioral uptake, or institutional consequences outside the platform?

If it scores zero on all four, it is a distribution story, not a significance story.

See my full guide and series for the deeper breakdown of this case and related tools.

Shift 5: Situate the incident in the pattern

Unlearn: Let one vivid case carry the argument about scale.

Relearn: Every incident needs a baseline, a trend line, and proportionality ( in both directions).

One vivid case can distort an entire public conversation. This happens constantly in coverage of online harm, extremism, and AI abuse: a single incident is treated as a trend, a trend is treated as a crisis, a crisis is reported without baseline data. Audiences end up with inflated fear, or false reassurance, and no way to judge what is actually escalating versus what is simply newly visible.

The proportionality failure runs in both directions, and both directions cause harm.

Inflating rare incidents produces moral panic, bad policy, and the kind of fear that bad actors deliberately manufacture. Minimizing widespread patterns produces public blindness to structural harm that is hiding in plain sight. Both failures serve bad actors: the first by manufacturing urgency around marginal threats, the second by providing cover for systemic ones.

Reporting the pattern means reporting both directions with equal rigor. How common is this, really? Is it rising, falling, or newly visible? Is this incident exceptional or representative? What would a reader need to know to make an accurate judgment about the scale and nature of the harm?

What this looks like in practice

Coverage of incel-linked violence regularly treats isolated attacks as evidence of a mass movement, inflating a rare incident into a pattern that the data doesn’t support. Coverage of Andrew Tate’s reach did the inverse: the Hope Not Hate finding that 8 in 10 boys aged 16 to 17 had seen his material, and the YouGov finding that 1 in 6 boys aged 6 to 15 held a positive view of him, were treated as fringe statistics in coverage that hadn’t done the work of situating the numbers. That is not a fringe statistic. Reporting it as one was a failure of proportionality in the opposite direction, minimizing a documented, widespread pattern because the number was uncomfortable to report at its actual scale.

The Marshall Project’s context-first reporting on crime data is the model for how to do this right: every incident is situated in the baseline, every trend is measured against historical data, and the story names clearly what the data shows and what it doesn’t. One dramatic incident never distorts the national picture because the national picture is always present in the reporting.

Editorial test:

Are you showing readers where this event sits in the real pattern — or are you allowing vividness to substitute for scale? Can you state, specifically: is this incident typical, exceptional, rising, falling, or simply newly visible?

If you can’t answer that question before you file, the context is missing.

Field note on these beats specifically:

The proportionality question is weaponized on both sides of these beats. Extremist actors inflate their own significance to appear more powerful and culturally dominant than they are. Treat their visibility claims with the same skepticism you’d apply to any source with an incentive to exaggerate. Platform harm is simultaneously minimized by the institutions that produce it. Treat their framing of harm as marginal or exceptional with the same skepticism. Your job is to find the actual baseline, which usually requires going outside the platform, outside the institution, and outside the most visible sources on both sides.

Use the context box. Add this to every spike story and every incident report on these beats:

• Baseline: what is the normal rate or scale of this type of incident or behavior?

• Trend line: is this rising, falling, stable, or newly visible?

• Rarity: is this exceptional or representative?

• Responsible inference: what can we actually conclude from this data, and what would we need to establish what we can’t yet conclude?

That box, applied consistently, prevents a single dramatic case from doing the work that evidence should do.

Toolkit 5: Context tools for situating incidents in pattern

For baseline and trend line data on online harm and extremism: the Global Network on Extremism and Technology (GNET) publishes research specifically designed to provide contextual data for journalists; the Center for Countering Digital Hate (CCDH) tracks platform harm at scale; Hope Not Hate’s annual State of Hate report provides UK and European baseline data on extremism reach and penetration.

For AI harm and platform data: the Stanford Internet Observatory, the Oxford Internet Institute, and the Alan Turing Institute all publish research that provides the baseline data most platform coverage lacks. Use them before you file, not after.

For proportionality in both directions: the Context Box above. Apply it to every spike story. If you can’t fill in all four fields, you don’t have enough information to report the incident as evidence of a pattern.

Pro tip: add the context box to every spike story: baseline, trend line, rarity, and what we can responsibly infer. It takes ten minutes and prevents the single most common framing failure on these beats.

See my full guide and series for the deeper breakdown of this case and related tools.

What these two shifts have in common, and how they complete Phase 1 (shifts and tips before reporting)

Both shifts are about the same underlying discipline: not letting the platform assign your story.

Shift 4 asks whether what is visible is actually significant. Shift 5 asks whether what is significant is being accurately sized. Together they close the two most common framing failures on these beats: treating virality as cultural evidence, and treating a single incident as proof of a pattern.

Combined with the first three shifts, Phase 1 is now complete. You know what story you’re telling (the system, not the spectacle), whose experience is at the center (the burden-bearers, not the perpetrators), what you’re following (consequence, not conflict), whether the platform signal is real (Shift 4), and whether the scale is accurate (Shift 5).

Phase 2 begins where Phase 1 ends. Once you know what you’re covering, how you gather and weigh evidence determines everything.

Please share your favorite tips and any additional shifts you think we should be making as media and human rights practitioners reporting on online harm. The shifts, tips and toolkits in this series are non-exhaustive, and are serve as a launching pad for this community, which includes YOU, to extract from as well as contribute to.

Because we care. And because we want to win. Collectively.

The Field

The practices above are easier to sustain inside a community of people working on the same problems than alone. That’s what The Field is: a cross-sector community of practice for journalists, researchers, advocates, lawyers, and technologists working at this intersection, built on the principle that the people with the most situational knowledge are often those with the least institutional power, and that better practice requires closing that gap deliberately. If this is your beat, wherever you are, it’s yours to join.

Join The Field: Fill out the intake form or reach out to me directly at inquiries@rajaalthaibani.com

The Frontier

Phase 1’s specific frontier question is the platform transparency problem: you can’t accurately situate incidents in pattern or audit virality if the platforms controlling the data don’t share it. Shifts 4 and 5 both require external data sources precisely because platform data is inaccessible, unreliable, or strategically curated. The EU Digital Services Act and US platform accountability efforts are the most significant structural responses to this problem, and both are currently contested, partially implemented, and under pressure. Naming that gap is part of what this guide does. Closing it requires more than better journalism. It requires platform accountability infrastructure that doesn’t yet exist at the scale these beats require.

Up next — Killing Spectacle, Part 2: Rigor Without Cruelty

Phase 1 is complete. Phase 2 is where the frame you built either holds or falls apart.

How to verify claims in spaces designed to mislead — including how to slow down when emotion spikes and bad actors are deliberately manufacturing urgency. How to build an evidence hierarchy rather than a transcript of competing claims. And how to use AI to see what only becomes visible at scale, rather than to produce faster noise.

Part 2 is where the craft gets specific. The frame is only as good as what you can prove.

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If this is your beat — or someone you edit, teach, or commission —send it directly and invite them to join The Field. The journalists and media practitioners who need this most are rarely the ones looking for it.

These aren’t universal rules. They’re practices drawn from years in this space. What works in a long-form investigation won’t always survive a breaking news brief. Context matters. This guide is a conversation, leave a comment or reach me directly with what’s missing and what works. What’s useful goes into the guide, with credit.

About the author. Raja Althaibani is an advisor, strategist, and trainer working at the intersection of human rights, media systems, digital evidence, and emerging technology. With over 15 years of experience across the Middle East, North Africa, and the United States, she has worked with journalists, civil society organizations, and international institutions to document harm, build accountability processes, and adapt human rights practice to shifting technological and political realities. She previously worked at WITNESS, the human rights organization specializing in video and digital documentation. She is the founder of Arab Hyphenated.

She writes Unembedded, which includes the ongoing series The Safari Is Over, and founded The Field, a cross-sector community of practice for journalists, researchers, advocates, and technical practitioners working on these beats.

inquiries@rajaalthaibani.com · www.rajaalthaibani.com · Join The Field

killing spectacle | media guide | virality | platform accountability | online harm | extremism | framing | Raja Althaibani

About the Author

Raja Althaibani works at the intersection of media, harm, technology, and accountability—advising, training, investigating, and building infrastructure for practitioners navigating an information landscape that moves faster than most frameworks can follow. Her background spans human rights, journalism, international law, and open-source digital documentation.

She writes Unembedded—long-form analysis, reported essays, and field frameworks on media, power, harm, and who controls the story. It includes two ongoing series: The Safari Is Over, on how media covers harm and what better practice looks like, and The Field Dispatch, the intelligence arm of The Field—a community of practice she founded.

Work with Raja: inquiries@rajaalthaibani.com · contact form · www.rajaalthaibani.com · Linkedin

The problems at the intersection of media, online harm, technology, and accountability don't respect disciplinary boundaries. Neither should the people working on them.

A journalist investigating an extremist network needs to understand platform infrastructure. A human rights lawyer building a case around digital evidence needs to understand how that evidence was collected and verified. A technologist building tools for open-source investigation needs to understand what practitioners in conflict zones can actually access and use. A researcher documenting online abuse needs to understand how newsrooms make editorial decisions, and what gets lost in translation between the field and the published piece. And a community documentarian on the ground needs to understand how her work will travel once it leaves her hands: who will interpret it, in what context, and toward what end.

These people rarely work together in any sustained way. The communities of practice1 that exist are largely siloed: by discipline, by geography and language, by institution, and by the structural imbalances that have long shaped who gets to lead, contribute, and be heard in this space.

The Field exists to change that.

What The Field is

The Field is a cross-sector community of practice (CoP)2, global from the start, for journalists, researchers, advocates, lawyers, and technical practitioners working at the intersection of media, harm, technology, and accountability.

It was founded on a simple argument: that the existing community of practice in this space is fractured, skewed toward Global North institutions, and structurally extractive toward the practitioners with the most situational knowledge and the least institutional power. That better outcomes— better journalism, stronger accountability, more effective tools, more durable practice require deliberate, unblocked collaboration across the full spectrum of the field.3

This is not a network. It’s a working community co-created, contribution-led, and designed to be less monopolized, more inclusive, and genuinely global.

What The Field does

The Field brings together practitioners to:

• Build shared knowledge across disciplines, geographies, and languages so that the journalist, the lawyer, the researcher, and the technologist are working from the same foundation rather than talking past each other.

• Develop practical frameworks and field guidance including methodologies, tools, and resources that are actually usable by the full range of people doing this work, not just those with institutional backing and Global North infrastructure.

• Strengthen the work that holds systems accountable by centering practitioners with situational knowledge, reducing extractive dynamics, and creating conditions for collaboration that is fair, equitable, and genuinely useful.

• Build a community of practice that lasts by connecting practitioners across sectors and geographies who are doing this work, sharing what they know, and building something more durable than any single investigation, report, or news cycle.

Who it’s for

If you work in any of the following, wherever you are in the world, The Field is for you:

Journalism and editorial practice · Open-source investigation and digital evidence · Human rights documentation and advocacy · International law and accountability · Disinformation and information disorder research · Platform policy and tech accountability · AI, emerging technology, and public interest practice · Media training and capacity building

This includes, and deliberately centers, practitioners from the so-called Global South (Global Majority), diaspora communities, and those working in and on conflict-affected and underrepresented contexts. The people closest to the harm are the ones this field most needs to hear from.

You don’t need an institutional affiliation. You don’t need to be based in a Global North city. You need to be doing the work, or building toward it.

Further Reading

The Field builds on arguments first made here: The Case To (Re)new Community of Practice for the Open Source Investigative Field — Symposium on Fairness, Equality, and Diversity in Open Source Investigations, OpinioJuris.

How to join

The Field is in its founding phase. This is the moment to get in early, shape what it becomes, and connect with the first cohort of practitioners building it together.

To join or express interest:

Fill in the intake form here

Reach out directly: inquiries@rajaalthaibani.com ; Or leave a comment below.

Tell us who you are, what you work on, where you’re based, and what you think The Field needs to do. That information will directly shape how the community is built.

There is no membership fee. No institutional gatekeeping. No prerequisite except the work.

Subscribe now

The Field was founded by Raja Althaibani. Read her work at Unembedded.

About the Author

Raja Althaibani works at the intersection of media, harm, technology, and accountability— advising, training, writing, investigating, and building the infrastructure that helps practitioners and institutions respond to an information landscape that moves faster than most frameworks can follow.

Her background spans human rights, journalism, international law and accountability, and open-source digital documentation. She works with journalists, editors, researchers, lawyers, advocates, technologists, and institutions across sectors and geographies, advising on online harm, information disorder, and emerging technology; training practitioners to work with greater rigor and judgment; and building cross-sector communities and tools designed to make the field stronger, more inclusive, and less extractive.

Her work is defined by one consistent thread: closing the gap between complex systems and the people who need to understand, navigate, and hold them accountable.

She writes Unembedded—long-form analysis, reported essays, practical guides, and field frameworks on media, power, harm, and who controls the story. It publishes original reporting, case studies, curated resources, tools and templates for practitioners, and research and reading lists across the beats it covers.

Unembedded includes two ongoing series: The Safari Is Over—on how media covers harm, extremism, and algorithmic culture, and what better practice looks like— and The Field Dispatch, the working intelligence arm of The Field community of practice. She is the founder of The Field.

Work with Raja: inquiries@rajaalthaibani.com or via contact form; and website www.rajaalthaibani.com

From Killing Spectacle: 15 Shifts for Reporting on Online Harm and Extremism, a guide for journalists, editors, producers, researchers, and media practitioners. Published here in parts. Each installment stands alone. The full picture builds across the series.

Killing Spectacle is part of ‘The Safari Is Over’, an ongoing series on media, harm, and the information landscape.

There’s a moment most journalists on this beat recognize, even if they don’t name it.

You’re pitching a story about a harmful online community, an AI abuse case, a radicalization pipeline. And somewhere in the process, the story migrates toward its most watchable part. The clip. The personality. The confrontation. The thing that makes an editor say: that.

It feels like journalism. It has texture and tension and a hook. But something has gone missing: the part that would actually change how the public understands what’s happening. The part that helps them identify where to direct action.

This guide is about that gap, and how to close it, deliberately.

What this guide is and isn’t

These are practices, not rules, drawn from years in this space, watching what holds and what collapses under scrutiny. They’re also shifts: things we have to actively unlearn before you can replace them with something more useful. Most of the bad instincts on this beat aren’t careless. They’re trained. They got rewarded. They got pieces commissioned and clips shared and panels booked. Unlearning them requires naming them first.

This is also a living document and a conversation. If you work on these beats— as a journalist, researcher, advocate, lawyer, technologist— what’s missing and what works belongs in here. Leave a comment or reach out directly. Everything useful goes into the guide, with credit.

How the full guide is structured

The 15 shifts are arranged across four phases: Framing (how you conceptualize and pitch the story before reporting begins), Rigor (how you verify and source in environments designed to mislead), Structure (how you shape and distribute the story without reproducing the harm), and Sustained Practice (how you protect and maintain this work inside institutions that don’t always reward it). The three shifts below are Phase 1. You don’t need to follow them sequentially, but the logic is cumulative, and each phase assumes the one before it.

The question that runs through all 15 shifts

Does this story increase public understanding, or does it redistribute attention?

Redistributing attention is easy. It generates clicks, and it can feel like exposure. But it rarely changes anything. Public understanding is harder to produce and harder to sell. It’s also the only thing journalism in this space can offer that the algorithm can’t.

What prompted this guide

This guide didn’t come from one story. It came from a pattern.

There is a structural problem in how online harm, extremism, and algorithmic culture get covered, and it shows up across formats, platforms, and beats. It’s not about bad journalists and storytellers. It’s about the gravitational pull of certain types of stories: ones that arrive pre-loaded with conflict, personality, and outrage, and make spectacle feel like investigation.

You know these stories.

The influencer radicalizing teenage boys, covered through his most inflammatory clips. The deepfake abuse case that leads with the viral moment and buries the policy vacuum. The AI system causing harm, reported as a curiosity rather than a systemic failure. The harassment campaign reconstructed around the abuser’s language rather than its cost to the target. The extremist community profiled through its most watchable members, never its recruitment infrastructure.

The Jihadi Johns and Andrew Tates—manufactured characters who understood exactly what the media would do with them, and built the spectacle, legitimacy, and reach they so desperately wanted accordingly. The alt-right figures who gamed outrage cycles to launder fringe ideology into mainstream debate. The misogynist podcasters whose revenue model runs on the very coverage claiming to expose them. The election disruptors who flood the zone knowing the correction will carry the lie further. The war crimes filmed and uploaded by perpetrators— state and non-state actors—because they knew journalists would distribute them.

In every case, the harmful actor understood the media environment better than the coverage did. And they know the media environment and its participants better than it knows itself.

These stories all have legitimate public interest at their core. The coverage often doesn’t find it because the spectacle is closer, faster, and easier to sell. That’s not a personal failure. It’s an editorial one.

And editorial choices can be made differently. This is a guide to making them differently: 15 shifts from spectacle-driven coverage to high-impact public interest reporting across online harm, extremism, AI, and algorithmic culture.

Shift 1: Pitch the system, not the spectacle

Unlearn: Anchor the pitch to a personality or incident.

Relearn: Pitch the system the incident reveals.

The most damaging instinct on this beat is reaching for a compelling figure or moment to sell a story. This is understandable, it’s how pitches get bought. But on beats involving harassment, extremism, or AI harm, incident-led coverage carries real costs: it re-traumatizes victims, amplifies the people causing harm, and normalizes what should remain structurally shocking. More practically: it produces stories that don’t survive the next news cycle. Incident-led coverage has a shelf life. System-led coverage has a subject.

What this looks like in practice

When AI-generated non-consensual images of a female student at a Louisiana middle school circulated last year, early coverage treated it as a conflict: a fight, an expulsion, a drama between teenagers. Readable. Thin.

Stronger reporting reframed the same facts around a policy vacuum: schools were applying outdated cyberbullying frameworks to a new type of harm and deepfake technology those laws never contemplated. No mechanism existed to respond, discipline, or protect. The incident was the entry point. The institution was the story.

One version ages out when the next incident lands. The other stays useful to every educator, parent, and policymaker who encounters the same gap. By focusing on the public-interest frame over spectacle, 8 more students were identified as victims of the same abuse, revealing a critical lack of oversight and accountability.

Editorial test:

Can you name the failing institution, platform, or policy in your first two paragraphs? If the story falls apart without the viral moment, you’re chasing spectacle.

Pitch frame to keep nearby:

The public needs to understand how [system] is responding to [harm] because it affects their ability to [protect themselves / hold someone accountable / make an informed decision].

Field note on AI and algorithmic beats specifically:

When a model or platform is implicated in harm, resist the pull toward anthropomorphizing the technology as the protagonist. The model isn’t the story. The decision to deploy it without safeguards, the gap between the terms of service and what the product actually does, the accountability structure that allowed the harm to scale, those are the story. Name the company. Name the design choice. Name the person who signed off.

Toolkit 1: Pitching the system when editors want the story

Before pitching, build a one-page map of the system you're investigating: the institution, the policy gap, the harm pathway, the people absorbing the cost. Kumu or a shared Miro board forces you to articulate the system before a word is written, and gives editors something concrete to look at beyond a clip or outrageous hook. AI-assisted document analysis (DocumentCloud Analyst, OCCRP Aleph) surfaces patterns across large document sets faster than manual reading. And maintain a running accountability file on the institutions on your beat (policy changes, enforcement actions, known gaps) so when an incident occurs, the system story is already half-reported.

*See my full guide and series for the deeper breakdown of this case and related tools.

Shift 2: Conflict is the delivery system. Consequence is the story.

Unlearn: Let the most dramatic moment become the unit of analysis.

Relearn: Treat conflict as the delivery system. Report the consequence.

Conflict generates heat, and heat generates clicks. But heat dissipates, and if you’ve only reported the confrontation, nothing survives the news cycle.

Covering consequence is different. Consequence is what changed. Who gained power, money, reach, or legitimacy. What the people most affected did next. How institutions responded or didn’t, or built in deniability so they wouldn’t have to.

What this looks like in practice

Podcast formats built around confrontation and humiliation, Fresh & Fit being a well-documented case, tend to get covered through their worst and most outrageous clips. That coverage is reliable and easy to produce. It also explains nothing.

But it doesn’t explain anything. It doesn’t tell you how the format generates revenue, how engagement mechanics reward escalation, how humiliation becomes entertainment, or what that does to the young men watching. Consequence-led reporting asks: what changed as a result of this? Who built a platform, a business, a political foothold? Who lost their safety, their sense of what’s normal? Who absorbed the cost?

That’s where the story lives.

Editorial test:

What happened after the conflict? Who gained, measurably (in reach, revenue, or legitimacy) and who absorbed the damage?

If you can’t answer both, the reporting isn’t finished.

Field note

Consequence is harder to report because it's often disaggregated and delayed. The influencer's revenue doesn't appear in the clip. The behavioral shift in the audience doesn't show up in the incident report. This is partly by design, platforms and bad actors alike benefit from keeping consequence invisible. Closing the gap requires a different sourcing strategy: researchers, platform transparency data, former employees, and the people most affected tracked over time, not quoted once. Phase 4 of this guide addresses the longitudinal obligation in full.

Toolkit 2: Following consequence when platforms obscure it

For platform and influencer revenue: Social Blade tracks estimated YouTube and Twitch earnings; SimilarWeb tracks audience growth and traffic sources; OpenCorporates surfaces corporate structures. For political influence: InfluenceMap. For moving from "here's the personality" to "here's the infrastructure": Gephi visualizes how content, accounts, and communities connect. For high-volume content beats, AI transcription (Whisper) and synthesis tools (NotebookLM) let you track rhetoric and escalation patterns across thousands of hours of material, the slow radicalization pipeline, not just the viral moment. And set calendar reminders at 3, 6, and 12 months after publication. The follow-up is itself a reporting method.

*See my full guide and series for the deeper breakdown of this case and related tools.

Shift 3: Center the burden-bearers, not the perpetrators

Unlearn: Let perpetrators set the terms of the story.

Relearn: Center the people who carry the long-term burden.

This is the structural failure that runs deepest, and the one most resistant to change because it’s baked into how stories get told.

On extremism, harassment, and abuse beats, perpetrators routinely set the frame. They’re quotable, accessible, often actively seeking coverage and eager for attention. Victims and survivors appear later : as context, as reaction, as proof that something bad happened. That structure isn’t neutral. It reproduces the hierarchy of the harm itself.

Centering burden-bearers isn’t a fairness question. It’s a reporting accuracy question. The people who live with the long-tail consequences of these systems understand them differently, and often more completely, than the people producing them. Their testimony is evidence. Not color.

What this looks like in practice

Amnesty International's Toxic Twitter research didn’t focus on what abusers said, it focused on what the abuse cost. Women changed how they used platforms. Many withdrew from public life online. Some feared for their physical safety offline. The damage was measurable, documented, and largely absent from coverage that kept returning to perpetrators and their rhetoric. That research made harm legible in terms institutions could act on. It named the hidden tax. It showed the invisible majority.

Editorial test:

Who has the most to lose in this story? Are they present with name, context, and consequence in the first third of your piece?

If not, you’re reporting the fire. Not the building that keeps catching.

Field note on source relationships

Burden-bearers are often sources who've been burned by coverage before: used as a single quote, stripped of context, left exposed after publication with no follow-up. The relationship requires more than a consent form. It requires transparency about how the material will be used, what decisions you'll make about their identification, and what your obligations are after the piece goes live. Phase 2 of this guide addresses this in depth, specifically, how to handle sources who are also subjects, and what rigor looks like without cruelty.

Toolkit 3: Reaching burden-bearers and protecting them

Secure communications are baseline: SecureDrop for newsrooms; Signal with disappearing messages for individual reporters. The Freedom of the Press Foundation's operational security guides are shareable with sources, not just practitioners. For community-based sourcing, the antidote to the parachute model, build relationships with survivor advocacy groups, mutual aid networks, and community organizations before you need them for a story. Meedan's Check enables collaborative verification with input from affected communities, valuable for content in languages or contexts outside a reporter's fluency. And the Dart Center for Journalism and Trauma carries peer-reviewed, practitioner-tested guidance on trauma-informed practice. It belongs in your working reference, not just your reading list.

*See my full guide and series for the deeper breakdown of this case and related tools.

What these three shifts have in common

They all require resisting the pull toward what is easiest to see, film, quote, and sell.

That pull is real. Editors want the hook. Platforms reward the clip. Audiences click on conflict. None of that is going away. And none of it is an excuse, either.

These shifts aren’t about producing slower journalism or quieter journalism. They’re about producing journalism with a longer half-life: stories that build public understanding instead of borrowing its attention.

Phase 1 of this guide is conceptual. It changes how you frame the story before you report it. The shifts in Phases 2, 3, and 4 build on this foundation: rigor without cruelty, structure that makes systems visible rather than personalities legible, and the sustained practice of doing this work inside institutions that don’t always reward it. A story with the right frame but weak verification is still a weak story. These phases are cumulative. Each one assumes the work of the one before.

Because I care—and because I want us to win—here are two bonus shifts to carry with you from Part I before you start reporting: treating virality as distribution evidence, and placing the incident within the larger pattern. Both are about closing the gap before the first word is written.

Killing Spectacle (Part I-Continued): Framing the Story — Two Bonus Shifts Before You Report on Online Harm and Extremism

Read it here.

The Field

The practices above are easier to sustain inside a community of people working on the same problems than alone. That’s what The Field is: a cross-sector community of practice for journalists, researchers, advocates, lawyers, and technologists working at this intersection, built on the principle that the people with the most situational knowledge are often those with the least institutional power, and that better practice requires closing that gap deliberately. If this is your beat, wherever you are, it’s yours to join.

Join The Field: Fill out the intake form or reach out to me directly at inquiries@rajaalthaibani.com

The Frontier

These three shifts will make individual stories better. They won’t fix the structural conditions that make better journalism hard to sustain: the revenue models that reward speed over depth, the synthetic media environment that is actively contaminating the evidentiary record, and the reach gap that means the reporting most needed by communities closest to the harm is the reporting least likely to reach them. Each of those problems gets its full treatment in the phase where it becomes most acute, synthetic media and verification in Part 2, the reach gap in Part 3, the revenue question in Part 4. Naming them here is a promise, not a deferral. The frontier is the reason the guide exists. Craft alone doesn’t close it.

Up next— Killing Spectacle, Part 2: Rigor without cruelty.

How to verify claims in spaces designed to mislead, including a synthetic media environment where the detection tools are always one cycle behind the fakes. How to handle sources who are also subjects, and what informed consent actually looks like as an ongoing practice rather than a one-time form. And the specific problem no one talks about clearly enough: what you do with evidence you can verify but cannot safely publish, and how that shapes what you can responsibly claim.

Part 2 of this guide is where the frame you built in Part 1 either holds or falls apart. The craft is in making it hold.

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Two additional shifts to consider before you start reporting: treating virality as distribution evidence, and placing the incident within the larger pattern. Both are about closing the gap before the first word is written.

Killing Spectacle (Part I-Continued): Frame the Story Right with Two More Shifts (read here)

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If this is your beat, or someone you edit, teach, or commission, send it to them directly and invite them to join The Field, our new community of practice. The journalists and media practitioners who need this most are rarely the ones looking for it.

These aren’t universal rules. They’re practices drawn from years in this space. What works in a long-form investigation won’t always survive a breaking news brief. Context matters. This guide is a conversation, leave a comment or reach me directly with what’s missing and what works. What’s useful goes into the guide, with credit.

About the author. Raja Althaibani works at the intersection of media, harm, technology, and accountability— advising, training, investigating, and building tools for practitioners navigating an information landscape that moves faster than most frameworks can follow.

She writes Unembedded, which includes the ongoing series The Safari Is Over ; and founded The Field, a cross-sector community of practice for journalists, researchers, advocates, and technical practitioners working on these beats.

inquiries@rajaalthaibani.com · www.rajaalthaibani.com · Join The Field