Election 2024 Security Monitoring: How Security Teams Tracked Threats Across Social Media

Election cycles concentrate risk. Threats against candidates, poll workers, election infrastructure, and public officials spike in volume, intensity, and specificity as election day approaches. The 2024 US election was no exception — and in many respects, the threat landscape was more complex than any prior cycle.

Social media was the primary theater. That’s where threats were made, coordinated, amplified, and — critically — where they could be detected earliest.

What Made 2024 Different

Several factors combined to make the 2024 election threat environment uniquely challenging.

Volume. The sheer quantity of election-related social media content overwhelmed manual monitoring approaches. Millions of posts per day mentioning candidates, polling locations, election procedures, and political grievances. Buried in that volume were genuine threat indicators — direct threats, location-specific coordination, and operational planning.

Platform fragmentation. Threats didn’t stay on one platform. A threat posted on X/Twitter might be amplified on Telegram, coordinated on Discord, and discussed on fringe forums. Monitoring a single platform meant missing the full picture.

AI-generated content. Deepfake videos, AI-generated images, and synthetic text appeared at scale for the first time in a US election cycle. Distinguishing authentic threats from AI-fabricated content added a new layer of complexity to threat assessment.

Doxing of election workers. Personal information about poll workers, election officials, and volunteers was published and shared across platforms — creating physical security risks for individuals who were simply doing their civic duty.

How Security Teams Approached It

Keyword and Entity Monitoring

Basic approach: monitor for mentions of specific candidates, election officials, polling locations, and election-related organizations. Layer in threat-specific language — direct threats, calls for violence, coded language used by extremist communities.

The challenge is false positive volume. The word “fight” appears in nearly every political post. AI-powered classification that distinguishes genuine threat language from metaphorical political speech is essential for making keyword monitoring usable at election-cycle volumes.

Geo-Fenced Monitoring Around Polling Locations

Critical for physical security teams. Set up geographic monitoring around every polling location, early voting site, and ballot counting facility. Social media posts from within those geographic areas surface potential threats — armed individuals approaching facilities, protest coordination, or crowd dynamics that could escalate.

This is where real-time monitoring provides its highest value. A post about armed individuals near a polling location needs a response in minutes, not hours.

Narrative Tracking

Election threats don’t emerge from nowhere. They build over weeks through narrative escalation — from grievance expression to dehumanizing rhetoric to operational planning. Tracking how narratives evolve provides early warning of potential violence before specific threats materialize.

Monitoring for narrative shifts — when a group moves from “the election is rigged” to “we need to take action” — is a leading indicator that operational security teams can act on.

Cross-Platform Correlation

A user posting on X/Twitter about “visiting” a specific polling location, combined with a Telegram message in a militia group discussing the same location, combined with a forum post asking about legal carry laws in that jurisdiction — individually, these might not trigger alerts. Correlated across platforms, they represent a credible threat picture.

Cross-platform correlation requires unified monitoring across data sources. Fragmented tools monitoring individual platforms miss these connections.

Lessons for Future Election Cycles

Start monitoring early. Threat indicators appear months before election day. Organizations that stood up monitoring in October missed weeks of pattern development.

Classify, don’t just collect. Raw volume of election content is unmanageable without AI classification. The monitoring infrastructure must separate genuine threat indicators from political speech at scale.

Coordinate with law enforcement. Election threats often require law enforcement response. Establish reporting channels and protocols before the threat volume spikes.

Monitor the aftermath. Election-related threats don’t stop on election day. Post-election periods — during counting, certification, and transition — can generate equal or greater threat activity.

DigitalStakeout provided real-time social media monitoring and AI-powered threat classification during the 2024 election cycle — tracking threats across platforms, classifying them against Physical Security, Public Safety, and Societal Risk domains, and delivering actionable intelligence to security teams in real time.

---

See how DigitalStakeout monitors event-driven threats. View the platform or get a demo.