social-media-trends-research

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---
name: social-media-trends-research
description: "Programmatic social media and marketing research using free tools: pytrends (Google Trends), yars (Reddit without API keys), and Perplexity MCP (Twitter/TikTok/Web). Use when finding trending topics in a niche, tracking keyword velocity and volume, monitoring Reddit discussions, discovering what's going viral, or researching content opportunities before writing. Zero-cost research stack with built-in rate limiting. Complements content-marketing-social-listening skill with executable code."
---

# Social Media Trends Research

## Overview

Programmatic trend research using three free tools:
- **pytrends**: Google Trends data (velocity, volume, related queries)
- **yars**: Reddit scraping without API keys
- **Perplexity MCP**: Twitter/TikTok/Web trends (via Claude's built-in MCP)

This skill provides executable code for trend research. Use alongside `content-marketing-social-listening` for strategy and `perplexity-search` for deep queries.

## Quick Setup

```bash
# Install dependencies (one-time)
pip install pytrends requests --break-system-packages
```

No API keys required. Reddit scraping uses public .json endpoints.

---

## Tool 1: pytrends (Google Trends)

### What It Provides
- Real-time trending searches by country
- Interest over time for keywords
- Related queries (rising = velocity indicators)
- Interest by region
- Related topics

### Basic Usage

```python
from pytrends.request import TrendReq
import time

# Initialize (no API key needed)
pytrends = TrendReq(hl='en-US', tz=330)  # tz=330 for India (IST)

# Get real-time trending searches
trending = pytrends.trending_searches(pn='india')
print(trending.head(20))
```

### Research Your Niche Keywords

```python
from pytrends.request import TrendReq
import time

pytrends = TrendReq(hl='en-US', tz=330)

# Define your niche keywords (max 5 per request)
keywords = ['heart health', 'cardiology', 'cholesterol']

# Build payload
pytrends.build_payload(keywords, timeframe='now 7-d', geo='IN')

# Get interest over time
interest = pytrends.interest_over_time()
print(interest)

# CRITICAL: Wait between requests to avoid rate limiting
time.sleep(3)

# Get related queries (THIS IS GOLD - shows rising topics)
related = pytrends.related_queries()
for kw in keywords:
    print(f"\n=== Rising queries for '{kw}' ===")
    rising = related[kw]['rising']
    if rising is not None:
        print(rising.head(10))
```

### Find Viral/Breakout Topics

```python
from pytrends.request import TrendReq
import time

pytrends = TrendReq(hl='en-US', tz=330)

def find_breakout_topics(keyword, geo=''):
    """Find topics with explosive growth (potential viral content)"""
    pytrends.build_payload([keyword], timeframe='today 3-m', geo=geo)
    time.sleep(3)  # Rate limiting
    
    related = pytrends.related_queries()
    rising = related[keyword]['rising']
    
    if rising is not None:
        # Filter for breakout topics (marked as "Breakout" or very high %)
        breakouts = rising[rising['value'] >= 1000]  # 1000%+ growth
        return breakouts
    return None

# Example usage
breakouts = find_breakout_topics('heart health', geo='IN')
print(breakouts)
```

### Rate Limiting Rules for pytrends

```python
import time

# SAFE: 1 request per 3-5 seconds for casual use
time.sleep(5)

# BULK RESEARCH: 1 request per 60 seconds
time.sleep(60)

# If you get rate limited (429 error): Wait 60-120 seconds, then continue
# If persistent issues: Wait 4-6 hours before resuming
```

### Useful Timeframes

| Timeframe | Use Case |
|-----------|----------|
| `'now 1-H'` | Last hour (real-time spikes) |
| `'now 4-H'` | Last 4 hours |
| `'now 1-d'` | Last 24 hours |
| `'now 7-d'` | Last 7 days (best for trends) |
| `'today 1-m'` | Last 30 days |
| `'today 3-m'` | Last 90 days (velocity analysis) |
| `'today 12-m'` | Last year (seasonal patterns) |

---

## Tool 2: Reddit (No API Keys - Public JSON Endpoints)

### What It Provides
- Search Reddit for any ke