Social Media Brand Monitor — Multi-Platform Mentions

Monitor your brand, product, or any keyword across Twitter/X, Reddit, YouTube, TikTok, Instagram, HackerNews, and Google News — all in a single actor run. Get a unified feed of every mention with sentiment analysis, engagement metrics, and analytics.

What it does

1. You provide a brand name or keyword (e.g., "Tesla", "OpenAI", "your-startup")
2. The actor searches across 5-7 social platforms simultaneously
3. Every mention is collected into a unified feed with:
   • Platform, author, content, date, URL
   • Engagement metrics (likes, shares, comments) normalized across platforms
   • Sentiment analysis (positive / negative / neutral)
4. You get analytics in the summary:
   • Mention volume by platform
   • Sentiment breakdown (% positive, negative, neutral)
   • Top influencers / most-engaged authors
   • Trending co-occurring topics

Use Cases

• PR & Crisis Management — Detect negative mentions early, track sentiment shifts in real-time
• Marketing & Brand Health — Measure share of voice, track campaign reception across platforms
• Competitor Analysis — Monitor competitor brands alongside your own
• Product Launch Tracking — See how your launch is received across every social channel
• Influencer Discovery — Find who's talking about your brand with the most engagement
• Market Research — Track industry keywords to spot trends before they go mainstream

Platforms Covered

Platform	Method	Data Collected
Twitter/X	Nitter instances + web search	Tweets, retweets, likes, replies
Reddit	old.reddit.com search	Posts, comments, scores, subreddits
YouTube	Search results parsing	Videos, views, likes, channel info
TikTok	Web search results	Videos, likes, shares, creator info
Instagram	Web search results	Posts, likes, comments, profiles
HackerNews	Algolia API (free, public)	Stories, comments, points, authors
Google News	News search parsing	Articles, publishers, dates

Input Parameters

Parameter	Type	Default	Description
brandName	string	required	Brand or keyword to monitor
platforms	array	all platforms	Which platforms to search
maxMentions	integer	500	Max mentions per platform
timeRange	enum	7d	How far back: 24h, 7d, 30d, all
includeSentiment	boolean	true	Run sentiment analysis
proxyConfiguration	object	none	Proxy settings (recommended)

Output Schema

Each mention in the dataset follows this unified schema:

{
  "platform": "reddit",
  "author": "techfan42",
  "authorUrl": "https://reddit.com/user/techfan42",
  "content": "Just tried OpenAI's new model and it's incredible...",
  "contentSnippet": "Just tried OpenAI's new model and it's incredible...",
  "title": "OpenAI releases GPT-5",
  "date": "2026-03-01T14:30:00.000Z",
  "url": "https://reddit.com/r/technology/comments/abc123",
  "engagement": {
    "likes": 342,
    "comments": 87,
    "shares": 12
  },
  "engagementScore": 441,
  "sentiment": "positive",
  "sentimentScore": 0.72,
  "brandName": "OpenAI",
  "scrapedAt": "2026-03-02T10:00:00.000Z"
}

Analytics Summary

After scraping, check the ANALYTICS key in the Key-Value Store for:

{
  "totalMentions": 1847,
  "volumeByPlatform": {
    "twitter": 523,
    "reddit": 412,
    "youtube": 287,
    "hackernews": 198,
    "google-news": 156,
    "tiktok": 142,
    "instagram": 129
  },
  "sentimentBreakdown": {
    "positive": 42.3,
    "neutral": 38.1,
    "negative": 19.6
  },
  "topAuthors": [
    { "author": "techcrunch", "platform": "google-news", "mentions": 12, "totalEngagement": 45000 }
  ],
  "trendingTopics": ["AI", "GPT-5", "machine learning", "AGI"],
  "timeRange": "7d",
  "scrapedAt": "2026-03-02T10:05:00.000Z"
}

Pricing

This actor uses Pay Per Event pricing:

• $0.005 per mention found — you only pay for results
• A typical brand monitoring run (500 mentions across 5 platforms) costs ~$2.50
• No charge for failed searches or duplicate filtering

Tips for Best Results

1. Use specific brand names — "Tesla Model Y" works better than just "Tesla"
2. Enable proxy — social platforms rate-limit aggressively; proxies ensure reliable results
3. Start with 7-day range — gives a good volume without being overwhelming
4. Schedule weekly — set up a recurring schedule to track brand health over time
5. Export to Google Sheets — use Apify's integration for a live brand monitoring dashboard

Technical Details

• Built with Apify SDK 3.x and Crawlee 3.x
• CheerioCrawler for efficient HTML parsing
• 10+ rotating user agents for anti-bot evasion
• Automatic deduplication across platforms
• Exponential backoff and retry on rate limits
• HackerNews uses official Algolia API (zero rate limits)
• Sentiment analysis via keyword-based NLP (no external API needed)

Changelog

• v1.0 (2026-03-02) — Initial release with 7 platform support