Apple’s WWDC 2025 event just wrapped up, and like many, I was curious to see how the community reacted especially on Reddit, where users tend to be brutally honest.
So I decided to spin up a quick sentiment analysis workflow using n8n, combining web scraping, text classification, and AI sentiment analysis to get a clear picture of how users actually felt about the announcements.
Why this matters
Whether you’re an SME or an enterprise, tracking real user sentiment after a product launch or major event is critical. This kind of analysis lets you:
- Measure community reaction in near real-time
- Understand user pain points or excitement
- Inform your marketing, PR, and product decisions
Requirements
- Reddit API or any other web scraping API . We will use bright data API
- Google sheets API
- AI models or your choice. We will use Gemini as its free
Setup
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We start by querying Reddit using the event name (e.g., WWDC 2025) as the keyword.
The data includes post titles, comments, subreddit names, and timestamps.
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Using a text classifier node, we eliminate off-topic noise and retain only posts actually discussing WWDC.
- Each relevant post is passed through Gemini to determine whether the sentiment is positive, neutral, or negative.
This can later be expanded to detect nuanced emotions like excitement, frustration, or sarcasm.
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- Finally, the classified data is pushed to Google Sheets for easy tracking, sharing, or even dashboarding via Looker Studio.
What did the community feel?
From the sample analyzed:
- A majority of users expressed disappointment, especially around software innovation and device upgrades.
- Only a minor segment was impressed, mostly praising developer tools or specific product details.
Here’s a quick peek:
I’ll be sharing a full n8n template for this use case you’ll be able to plug in your own event name, platform, or product and analyze reactions instantly.
Happy productivity!!
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