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displayed_sidebar: developersSidebar
---
# Video Channel Discovery: Current State & Enhancement Plan
## Executive Summary
**Question:** Does this repo look at local government websites and attempt to discover their YouTube, Facebook, or other video channels?
**Answer:**
- β **Currently NO** - The repo does NOT scrape government websites for social media links
- β
**Partially YES** - It extracts video URLs from pre-existing datasets (MeetingBank, Open States)
- β
**NEW** - We've created `social_media_discovery.py` to implement your suggestion
---
## Current State: What Exists
### β
Video Discovery from Datasets (Offline Sources)
**1. MeetingBank (HuggingFace)**
- **File:** [`discovery/meetingbank_ingestion.py`](../discovery/meetingbank_ingestion.py)
- **Status:** β
**Working** - Video URLs ARE being extracted
- **Coverage:** 1,366 meetings from 6 cities
- **Video Sources:**
- YouTube URLs (extracted from `urls['youtube_id']`)
- Vimeo URLs (extracted from `urls['vimeo_id']`)
- Archive.org collections (alameda, boston, denver, king-county, long-beach, seattle)
**2. Open States (API)**
- **File:** [`discovery/openstates_sources.py`](../discovery/openstates_sources.py)
- **Status:** β
Working
- **Coverage:** 50+ state legislatures
- **Extracts:** YouTube channels, Vimeo accounts, Granicus portals from jurisdiction metadata
**3. City Scrapers (GitHub)**
- **File:** [`discovery/city_scrapers_urls.py`](../discovery/city_scrapers_urls.py)
- **Status:** β οΈ Partial - extracts start_urls but not video links yet
- **Coverage:** 100-500 agencies from Chicago, Pittsburgh, Detroit, Cleveland, LA
- **Note:** Granicus video pages with embedded YouTube, but extraction not fully implemented
### β What's Missing: Website Scraping for Social Media
**Current Gap:**
The repo discovers government homepage URLs but does NOT:
1. β Scrape those websites for social media links
2. β Extract YouTube/Facebook channels from footers
3. β Check "Contact Us" or "About" pages
4. β Use USA.gov or federal aggregators
**Existing Homepage Discovery:**
- **File:** [`discovery/url_discovery_agent.py`](../discovery/url_discovery_agent.py)
- **What it does:**
- β
Finds government homepage URLs using GSA .gov registry
- β
Tests URL patterns (cityname.gov, etc.)
- β
Crawls to find minutes/agenda pages
- β **But does NOT look for social media links**
---
## Your Suggestion: Federal Aggregators & Website Scraping
### Excellent Ideas!
#### 1. USA.gov Local Directory
```
β
Most accurate way to verify channels are legitimate
β
Provides official website for every city/county
β
Most governments link social media in footer/contact sections
```
**Implementation:** See section below on how to integrate.
#### 2. USA.gov/archive (Federal Videos)
```
β οΈ Good for federal agencies
β οΈ Limited local government coverage
β
Could supplement state-level sources
```
**Use Case:** State agencies and federal programs that touch local policy.
---
## NEW Implementation: Social Media Discovery
We've created a new module to implement your suggestion!
### File: `discovery/social_media_discovery.py`
**What it does:**
1. β
Takes government homepage URLs (from existing discovery)
2. β
Scrapes footer sections for social media links
3. β
Checks common contact/about pages
4. β
Extracts YouTube, Facebook, Vimeo, Archive.org, Granicus
5. β
Validates and cleans URLs
6. β
Batch processing for hundreds of jurisdictions
**Example Usage:**
```python
from discovery.social_media_discovery import SocialMediaDiscovery
jurisdictions = [
{
'jurisdiction_id': 'seattle-wa',
'homepage_url': 'https://www.seattle.gov',
'jurisdiction_name': 'Seattle',
'state': 'WA'
}
]
async with SocialMediaDiscovery() as discovery:
results = await discovery.discover_batch(jurisdictions)
# Results:
# [
# {
# 'jurisdiction_name': 'Seattle',
# 'social_media': {
# 'youtube': ['https://www.youtube.com/@cityofseattle'],
# 'facebook': ['https://www.facebook.com/CityofSeattle'],
# 'twitter': ['https://twitter.com/CityofSeattle']
# },
# 'platform_count': 3,
# 'total_urls': 3
# }
# ]
```
**Detection Strategy:**
- Focus on footer sections (most reliable)
- Common CSS selectors: `footer`, `[class*="footer"]`, `[class*="social"]`
- Pattern matching for platform URLs
- Validates against known domain patterns
---
## Integration with Existing Pipeline
### How Social Media Discovery Fits In
```
1. URL Discovery Agent (EXISTING)
ββ> Finds government homepage URLs
ββ> Uses GSA .gov registry
ββ> Pattern matching (cityname.gov)
ββ> Validates URLs
2. Social Media Discovery (NEW) β¬
οΈ Add this step
ββ> Scrapes homepages for social links
ββ> Checks footer sections
ββ> Checks contact/about pages
ββ> Extracts YouTube, Facebook, etc.
3. Meeting Scraper (EXISTING)
ββ> Uses discovered URLs to scrape meetings
```
### Integration Code Example
```python
from discovery.url_discovery_agent import URLDiscoveryAgent
from discovery.social_media_discovery import SocialMediaDiscovery
from discovery.gsa_domains import load_gsa_domains
# Step 1: Discover government websites
gsa_domains = load_gsa_domains()
url_agent = URLDiscoveryAgent(gsa_domains)
jurisdictions = [...] # From Census data
discovered_urls = await url_agent.discover_batch(jurisdictions)
# Step 2: NEW - Discover social media from those websites
social_discovery = SocialMediaDiscovery()
social_results = await social_discovery.discover_batch(discovered_urls)
# Step 3: Save to Bronze layer
save_to_bronze_layer(social_results, "social_media_channels")
```
---
## USA.gov Integration Guide
### Approach 1: Use USA.gov Local Directory as Homepage Source
**What USA.gov Provides:**
- Official .gov website for every city/county
- Most authoritative source for homepage URLs
- Can replace/supplement GSA domain matching
**Implementation:**
```python
# discovery/usa_gov_directory.py (NEW FILE TO CREATE)
import httpx
from bs4 import BeautifulSoup
async def get_usa_gov_local_directory():
"""
Scrape USA.gov local directory for official city/county websites.
USA.gov maintains a directory at:
https://www.usa.gov/local-governments
Each state page lists cities/counties with official websites.
"""
base_url = "https://www.usa.gov/local-governments"
# 1. Get list of states
# 2. For each state, get list of cities/counties
# 3. Extract official website URLs
# 4. Return structured data
pass # Implementation details
# Then use in url_discovery_agent.py:
def _match_usa_gov_directory(jurisdiction_name, state):
"""
Match jurisdiction to USA.gov directory entry.
Higher confidence than pattern matching because it's
verified by federal government.
"""
usa_gov_url = lookup_usa_gov_directory(jurisdiction_name, state)
if usa_gov_url:
return (usa_gov_url, 0.98) # Very high confidence
return None
```
### Approach 2: USA.gov/archive for Federal Video Content
**Use Case:** State health departments, federal programs
```python
# discovery/federal_video_sources.py (NEW FILE TO CREATE)
FEDERAL_VIDEO_CHANNELS = {
"cdc": {
"youtube": "https://www.youtube.com/@CDCgov",
"topics": ["public_health", "oral_health"]
},
"hrsa": {
"youtube": "https://www.youtube.com/@HRSAgov",
"topics": ["health_centers", "dental_programs"]
},
"state_health_depts": {
# Each state's health department
"CA": "https://www.youtube.com/@CAPublicHealth",
"TX": "https://www.youtube.com/@TXHealthHumanServices",
# ... all 50 states
}
}
def get_federal_video_sources():
"""
Get federal agency video channels relevant to oral health policy.
Sources:
- usa.gov/archive featured channels
- State health departments
- CDC, HRSA, CMS channels
"""
pass
```
### Approach 3: ELGL Top YouTube Channels (NEW - HIGHLY RECOMMENDED!)
**What:** ELGL (Engaging Local Government Leaders) publishes curated "Top Local Government YouTube Channels" lists
**Why This is Excellent:**
```
β
Curated by experts (not automated scraping)
β
Highlights MOST ACTIVE channels
β
Quality > Quantity approach
β
Updated annually
β
Covers innovative local governments nationwide
```
**Sources:**
- ELGL Blog: https://elgl.org/
- Annual "Top Local Gov YouTube Channels" articles
- Digital innovation showcases
**Expected Coverage:** 50-100 top-tier channels (most active, highest quality)
**Implementation:** See `discovery/curated_sources.py`
### Approach 4: NACo County Database (NEW - COMPREHENSIVE!)
**What:** National Association of Counties maintains database of all 3,143 U.S. counties
**Why This is Excellent:**
```
β
Complete county coverage (all 3,143 counties)
β
Official website URLs verified by NACo
β
Digital innovation showcase
β
Authoritative source for county data
β
Partnership opportunities
```
**Sources:**
- NACo County Explorer: https://ce.naco.org/
- Digital Counties Survey
- NACo Communications Awards
**Expected Coverage:** 3,143 counties with official websites
**Implementation:** See `discovery/curated_sources.py`
---
## Complete Implementation Plan
### Phase 1: Enhance Existing Dataset Extraction (β
DONE)
- [x] MeetingBank video URLs (already working)
- [x] Open States channels (already working)
- [ ] City Scrapers Granicus video extraction (TODO)
### Phase 2: Website Social Media Discovery (β
NEW MODULE CREATED)
**Implementation:**
1. [x] Create `social_media_discovery.py` module
2. [ ] Test on sample cities (Seattle, Chicago, Austin)
3. [ ] Integrate with URL discovery pipeline
4. [ ] Write to Bronze layer: `bronze/social_media_channels`
**Tasks:**
```bash
# Test the new module
cd discovery
python social_media_discovery.py
# Expected output: YouTube, Facebook, Vimeo URLs for test cities
```
### Phase 3: USA.gov Integration (RECOMMENDED)
**Priority: HIGH** - Most authoritative source
**Tasks:**
1. [ ] Create `discovery/usa_gov_directory.py`
2. [ ] Scrape USA.gov local directory for official URLs
3. [ ] Use as primary source (confidence 0.98)
4. [ ] Fallback to pattern matching for missing entries
**Estimated URLs:**
- ~3,000 cities/counties with verified .gov URLs
- ~10,000+ municipalities (including .org, .us domains)
### Phase 4: ELGL Curated Channels (NEW - HIGH PRIORITY!)
**Priority: HIGH** - Quality over quantity
**Tasks:**
1. [x] Create `discovery/curated_sources.py` β
2. [ ] Scrape ELGL "Top YouTube Channels" articles
3. [ ] Parse channel URLs and metadata
4. [ ] Flag as "top-ranked" in database
**Expected Results:**
- 50-100 most active local government channels
- High-quality, verified content
- Innovative digital communication examples
**Why This Matters:**
These are the channels with the MOST meeting videos and BEST production quality!
### Phase 5: NACo County Database (NEW - HIGH PRIORITY!)
**Priority: HIGH** - Comprehensive county coverage
**Tasks:**
1. [x] Create `discovery/curated_sources.py` β
2. [ ] Contact NACo for data partnership/export
3. [ ] Integrate NACo County Explorer data
4. [ ] Scrape digital innovation showcase
5. [ ] Cross-reference with GSA .gov domains
**Expected Results:**
- All 3,143 U.S. counties with official websites
- Digital innovation leaders identified
- County media hub URLs
**Partnership Opportunity:**
NACo may provide bulk data export or API access for research/public benefit projects.
### Phase 6: Federal Video Aggregators (OPTIONAL)
**Priority: MEDIUM** - Supplementary source
**Tasks:**
1. [ ] Create `discovery/federal_video_sources.py`
2. [ ] Compile federal agency channels (CDC, HRSA, etc.)
3. [ ] Compile state health department channels (all 50 states)
4. [ ] Add to video sources table
**Use Case:** State-level policy analysis, federal program tracking
---
## Testing & Validation
### Test the New Social Media Discovery
```bash
# 1. Install dependencies
pip install httpx beautifulsoup4
# 2. Run standalone test
cd /home/developer/projects/open-navigator
python discovery/social_media_discovery.py
# Expected output:
# β Found 3 social media links for Seattle
# youtube: 1 URLs
# facebook: 1 URLs
# twitter: 1 URLs
# β Found 2 social media links for Chicago
# youtube: 1 URLs
# facebook: 1 URLs
```
### Integration Test
```python
# Full pipeline test
from discovery.discovery_pipeline import DiscoveryPipeline
pipeline = DiscoveryPipeline()
# 1. Discover jurisdictions (Census data)
# 2. Discover homepage URLs (GSA + patterns)
# 3. NEW: Discover social media (footer scraping)
# 4. Write all to Bronze layer
results = await pipeline.run_full_pipeline(
limit=100,
include_social_media=True # NEW FLAG
)
```
---
## Performance & Scalability
### Current Approach (Dataset-Only)
- β
Fast (no web requests)
- β
Reliable (static datasets)
- β Limited coverage (only cities in datasets)
- β Stale data (datasets not updated frequently)
### New Approach (Website Scraping)
- β οΈ Slower (requires web requests)
- β οΈ Less reliable (websites change)
- β
Comprehensive coverage (all cities with websites)
- β
Fresh data (real-time discovery)
### Hybrid Strategy (RECOMMENDED)
1. **Start with datasets** (MeetingBank, Open States)
- Get 1,366 meetings with videos immediately
- High confidence, validated data
2. **Supplement with website scraping**
- Fill gaps for cities not in datasets
- Discover newly created channels
- Verify dataset URLs are still valid
3. **Use USA.gov for verification**
- Highest confidence for homepage URLs
Curated Lists (NEW - YOUR SUGGESTIONS!):**
- ELGL Top Channels: 50-100 most active channels π₯
- NACo Counties: 3,143 counties with official websites π₯
- NACo Digital Innovation: ~100 innovative counties
**Website Scraping Discovery (NEW):**
- Major cities (100+ population): ~300 cities with YouTube
- Medium cities (50k-100k): ~500 cities with social media
- All municipalities: ~3,000-5,000 with public video channels
**Total Potential:**
- **3,000-5,000 YouTube channels** for meeting videos
- **50-100 TOP-TIER channels** (ELGL curated) π
- **3,143 county websites** (NACo database) π
- **1,000+ Granicus portals** with embedded videos
- **500+ Vimeo accounts**
- **10,000+ Facebook pages** (may have video links)
**Quality Tiers:**
1. **Tier 1 (Highest):** ELGL Top Channels - most active, best quality
2. **Tier 2 (High):** NACo Digital Innovation - county leaders
3. **Tier 3 (Good):** MeetingBank/Dataset channels - verified content
4. **Tier 4 (Discovery):** Website scraping - newly discoveredideo URLs
# Priority 2: USA.gov verified (high confidence)
usa_gov_cities = [...] # ~3,000 verified .gov sites
# Priority 3: Website scraping (for gaps)
remaining_cities = [...] # ~87,000 jurisdictions
# Parallel processing
async def process_batch(cities, batch_size=50):
for i in range(0, len(cities), batch_size):
batch = cities[i:i+batch_size]
results = await social_discovery.discover_batch(batch)
save_to_bronze(results)
await asyncio.sleep(5) # Rate limiting
```
---
## Expected Outcomes
### Coverage Estimates
**Dataset-Based Discovery:**
- MeetingBank: 6 cities β
- Open States: 50+ state legislatures β
- City Scrapers: 100-500 agencies β οΈ (need to extract video links)
**Website Scraping Discovery (NEW):**
- Major cities (100+ population): ~300 cities with YouTube
- Medium cities (50k-100k): ~500 cities with social media
- All municipalities: ~3,000-5,000 with public video channels
**Total Potential:**
- **3,000-5,000 YouTube channels** for meeting videos
- **1,000+ Granicus portals** with embedded videos
- **500+ Vimeo accounts**
- **10,000+ Facebook pages** (may have video links)
---
## Next Steps
### Immediate Actions (This Week)
1. **Test Social Media Discovery** β
READY TO RUN
```bash
python discovery/social_media_discovery.py
```
2. **Integrate with Pipeline**
- Add to `discovery_pipeline.py`
- Write results to Bronze layer
- Create `bronze/social_media_channels` table
3. **Document Integration**
- Update README with social media discovery
- Add examples to documentation
### Short-term (Next 2 Weeks)
1. **USA.gov Integration**
- Create `usa_gov_directory.py`
- Scrape local directory
- Use as primary URL source
2. **Enhanced MeetingBank Extraction**
- Extract all video URLs from `urls` dictionary
- Test on all 1,366 meetings
- Validate YouTube links are still active
3. **City Scrapers Video Links**
- Update `city_scrapers_urls.py`
- Extract Granicus video URLs
- Crawl Granicus pages for embedded YouTube
### Long-term (Next Month)
1. **Federal Aggregators**
- USA.gov/archive integration
- State health department channels
- CDC/HRSA video collections
2. **Automated Validation**
- Check if discovered channels still exist
- Verify channels have meeting content
- Score channels by video count and relevance
3. **Scale to 1,000+ Cities**
- Batch processing framework
- Parallel scraping with rate limiting
- Delta Lake storage for discovered channels
---
## Conclusion
### Summary
**Current State:**
- β
Video URLs extracted from datasets (1,366 meetings)
- β No website scraping for social media links
- β No USA.gov integration
**Your Suggestion:**
- β
**Excellent idea!** Website scraping is the missing piece
- β
USA.gov provides most authoritative homepage URLs
- β
Footer/contact page scraping will find channels
**Implementation:**
- β
Created `social_media_discovery.py` module
- β
Ready to test and integrate
- β
USA.gov integration guide provided
- β
Full roadmap for 1,000+ city coverage
**Impact:**
Going from 6 cities with video URLs to **3,000-5,000 cities with YouTube channels** will dramatically increase the reach of the Oral Health Policy Pulse system!
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