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Brand Threat Intelligence: Stop Fake Outrage Before It Hits Your Brand

How to Protect Campaigns and Markets from Inauthentic Narratives


Brand Threat Intelligence: Fake profiles employed two primary methods: amplifying each other to simulate popularity and blending into authentic conversations to appear credible.
Brand Threat Intelligence: Fake profiles employed two primary methods: amplifying each other to simulate popularity and blending into authentic conversations to appear credible.

What is Brand Threat Intelligence?


TL;DR: Brand Threat Intelligence detects fake accounts, bot-driven outrage, and harmful narratives, enabling your brand to act before a crisis goes viral. We offer a service and/or the software platform of our partner and market leader Cyabra, so that you can conduct research with our assistance or independently. #what


Evidence:

  • American Eagle case: 272 fake TikTok accounts generated 77,000+ boycott engagements in 3 days.

  • DeepSeek case: 15% of profiles hyping adoption were bots, distorting investor perception.

  • Fake activity spreads faster than authentic content — outpacing the regular monitoring of comms teams.

  • In terms of the complete analysis, including authenticity analysis (fake vs real accounts), we monitor X, Facebook, TikTok, and Instagram. For the rest of the analysis, excluding authenticity (fake or real?), we also monitor YouTube, Telegram (open channels), Reddit, VK, and Baidu (we can also analyze impersonations on LinkedIn).



Why can’t social listening solve this?


TL;DR: Social listening measures sentiment, but not whether the voices are real or fake. #why


Evidence:

  • The platform of our partner Cyabra complements social listening: it detects authenticity of accounts, not just volume.

  • Semantic analysis reveals which narratives are being hijacked, not just how often they appear.

  • Early warning = stopping reputational damage before it trends on hashtags.



What are the early warning signs to monitor?


TL;DR: Six red flags indicate when a campaign is being hijacked. #criteria


Evidence:

  1. Disproportionate spikes in negative narratives

  2. Sudden reinterpretation of slogans or brand cues

  3. Clusters of look-alike accounts posting in sync

  4. Engagement driven by fringe influencers

  5. Boycott calls are spreading faster than product talk

  6. Cross-platform anomalies (e.g., sudden TikTok floods)



Build vs. Buy: Can brands do this in-house?


TL;DR: Detection requires cross-platform data and AI expertise — faster to adopt specialised tools. #build


Evidence:

  • In-house = long build cycles, data access hurdles, and missed crises.

  • SaaS tools surface risks in hours, not months.

  • Cost trade-off: one missed false negative can outweigh years of licensing.



What does a 90-day rollout look like?


TL;DR: Monitor → Simulate → Act. #rollout


Evidence:

  • 0–30 days: Integrate monitoring and set thresholds.

  • 31–60 days: Run “war-game” disinformation scenarios with PR/legal.

  • 61–90 days: Establish playbooks for public response, influencer engagement, and corrective narratives.



FAQ

  1. Is all backlash disinformation? → No — but fake accounts amplify real concerns.

  2. Which platforms are riskiest? → TikTok & X, due to speed and weak controls.

  3. Do detection tools replace PR? → No, they empower PR with faster intelligence.

  4. Can smaller brands be hit? → Yes, bots don’t care about company size.

  5. Can sentiment recover? → Yes, if the response is early and transparent.




Book a demo to see how we protect your brand from fake outrage before it trends.


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