Using AI to Catch Emotional Shifts Before Crisis Hits
A brand's reputation can change in the blink of an eye, often triggered by a single tweet or campaign misstep. Emotional reactions spread quickly online, and if PR teams don’t respond just as fast, negative sentiment can spiral out of control.
Bianca Prade, CEO of BStrategies and visiting scholar at George Washington University, highlights how AI-driven sentiment monitoring can help teams tell apart mere noise from genuine shifts in public feeling. She points to Coca-Cola’s AI-generated holiday film as a recent example: social sentiment flipped from praise to concern in just over an hour. Consumers and artists criticized the visuals as “soulless” and worried about AI replacing human creativity. The brand’s slow response allowed negative narratives to take hold, showing how crucial real-time insight and quick action are.
Prade will lead a session called “From Sentiment to Strategy” at The PR Daily Conference, emphasizing how spotting emotional shifts early allows PR teams to react smarter and faster. “Catch emotion dips early or risk losing control of the story,” she warns.
Best Practices for AI in Sentiment Analysis
Instead of chasing viral hashtags or raw mention counts, Prade’s team focuses on the velocity and intensity of sentiment changes. For example, five angry tweets from verified accounts within 15 minutes can be far more telling than hundreds of neutral mentions throughout the day.
To reduce false alarms, their AI clusters emotion words to detect sarcasm or exaggeration. Once a sentiment shift is detected, they map the top emotions to a story frame—for instance, anger often signals a justice narrative, while joy suggests a celebration angle.
They use a simple “traffic-light” alert system to guide action:
- Green: Sentiment steady or rising, no action needed
- Yellow: Small dip, monitor and prepare a response
- Red: Sharp drop, activate rapid-response measures
This method supports quick, nuanced decisions as digital conversations fragment and emotions spike. For example, when an AI tool flagged rising frustration after a course price hike on a private platform, the team paused promotions, hosted an Ask-Me-Anything session with the instructor, and offered a limited early-bird discount. Positivity bounced back within 48 hours, and sign-ups returned to plan.
For teams getting started, Prade suggests running a small pilot: track sentiment on a live campaign using a basic tool, set alerts for sudden shifts, assign someone to monitor, and document triggers and responses. A practical success like this can make a stronger case for budget than theoretical reports.
Don’t Lose Sight of the Human Factor
While setting up AI-driven moderation, Prade discovered that blending AI’s pattern recognition with human judgment improves outcomes. Their moderators review AI suggestions daily, adjust tone to match brand voice, and add context where needed. This approach boosted engagement because community members quickly noticed the difference.
AI tools have limits—they struggle with small data sets, niche jargon, and sarcasm in memes or videos. Communicators should avoid declaring trends based on too few mentions and always combine AI findings with human insight.
Transparency is key. Prade advises telling clients when AI is part of the process to build trust and accountability. Looking ahead, multimodal sentiment analysis that incorporates voice and video cues alongside text shows promise. However, caution is needed with opaque “black-box” AI models that don’t reveal training data. Human quality assurance must advance alongside technology.
The PR Daily Conference will be held May 21-23 in Washington, D.C.
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