124 lines
No EOL
4.2 KiB
Markdown
124 lines
No EOL
4.2 KiB
Markdown
# LinkedIn Enrichment Summary for Eye Filmmuseum
|
|
|
|
## What We've Accomplished
|
|
|
|
### 1. ✅ Created LinkedIn Extraction Scripts
|
|
- **`extract_linkedin_profiles.py`** - Basic extraction
|
|
- **`extract_linkedin_profiles_v2.py`** - Improved extraction
|
|
- **`linkedin_comprehensive_extraction.py`** - Comprehensive extraction
|
|
- **`linkedin_ultimate_extraction.py`** - Ultimate deep extraction
|
|
- **`enrich_linkedin_ultimate.py`** - API enrichment script (ready)
|
|
|
|
### 2. ✅ Successfully Extracted LinkedIn Profiles
|
|
|
|
**Total LinkedIn URLs Found: 42**
|
|
- Personal profiles: 41
|
|
- Company profiles: 1 (Eye Film Institute Netherlands)
|
|
- Unknown names: 0 (all identified)
|
|
|
|
### 3. 📊 Breakdown by Section
|
|
|
|
| Section | Profiles Found |
|
|
|---------|---------------|
|
|
| Management | 3 |
|
|
| Board of Trustees | 1 |
|
|
| Department Heads | 4 |
|
|
| Former Directors | 1 |
|
|
| Chief Curator | 1 (+4 in foaf_knows) |
|
|
| Collection Specialists | 9 |
|
|
| Curators | 5 |
|
|
| Archivists & Film Specialists | 4 |
|
|
| Programmers | 2 |
|
|
| PICO Staff | 2 |
|
|
| Deceased Staff | 1 |
|
|
| Volunteers & Interns | 4 |
|
|
| Conservators & Art Handlers | 3 |
|
|
| Company Page | 1 |
|
|
|
|
### 4. 📁 Files Created
|
|
|
|
1. **Main enriched YAML**: `NL-NH-AMS-U-EFM-eye_filmmuseum_linkedin_ultimate.yaml`
|
|
- Contains all original data + LinkedIn extraction structure
|
|
- Ready for API enrichment
|
|
|
|
2. **Profiles JSON**: `NL-NH-AMS-U-EFM-eye_filmmuseum_linkedin_ultimate_all_profiles.json`
|
|
- Clean list of all 42 LinkedIn profiles
|
|
- Easy to parse for API calls
|
|
|
|
3. **Profiles CSV**: `NL-NH-AMS-U-EFM-eye_filmmuseum_linkedin_ultimate_profiles_ultimate.csv`
|
|
- Spreadsheet-friendly format
|
|
- Columns: Name, LinkedIn URL, Type, Path, Field, Confidence
|
|
|
|
4. **Report JSON**: `NL-NH-AMS-U-EFM-eye_filmmuseum_linkedin_ultimate_ultimate_report.json`
|
|
- Detailed extraction statistics
|
|
- File locations and metadata
|
|
|
|
### 5. 🚀 Ready for API Enrichment
|
|
|
|
The **`enrich_linkedin_ultimate.py`** script is ready to:
|
|
- Fetch detailed profile data for all 42 LinkedIn URLs
|
|
- Extract: name, headline, location, industry, summary
|
|
- Get: connection count, experience, education, skills
|
|
- Handle rate limiting (5 profiles per batch, 3-second delays)
|
|
- Try multiple API endpoints for reliability
|
|
|
|
### 6. 🔧 To Complete Enrichment
|
|
|
|
1. **Get Unipile API credentials**:
|
|
```bash
|
|
# Sign up at https://dashboard.unipile.com/signup
|
|
export UNIPILE_API_KEY=your_api_key_here
|
|
export UNIPILE_DSN=api1.unipile.com:13111
|
|
```
|
|
|
|
2. **Run enrichment**:
|
|
```bash
|
|
python scripts/enrich_linkedin_ultimate.py
|
|
```
|
|
|
|
3. **Expected output**:
|
|
- `NL-NH-AMS-U-EFM-eye_filmmuseum_linkedin_ultimate_enriched.yaml`
|
|
- All 42 profiles enriched with detailed LinkedIn data
|
|
- Full integration into existing Eye Filmmuseum structure
|
|
|
|
### 6.1 ✅ Scripts Ready
|
|
|
|
- **`enrich_linkedin_ultimate.py`** - Fixed and ready for API enrichment
|
|
- Handles rate limiting (5 profiles per batch)
|
|
- Tries multiple API endpoints for reliability
|
|
- Creates comprehensive enrichment reports
|
|
- Integrates data back into main YAML file
|
|
|
|
### 7. 📈 Sample Profiles Found
|
|
|
|
Notable staff with LinkedIn:
|
|
- **Maral Mohsenin** (Management)
|
|
- **Giovanna Fossati** (Chief Curator)
|
|
- **Patricia Pisters** (foaf_knows network)
|
|
- **Dan Streible** (foaf_knows network)
|
|
- **Nanna Verhoeff** (foaf_knows network)
|
|
- **Rommy Albers** (Collection Specialist & Curator)
|
|
- **Lou Burkart** (Collection Specialist & Curator)
|
|
- **Anne Gant** (Department Head)
|
|
- **Frank Roumen** (Department Head)
|
|
- **Susan van Gelderen** (Department Head)
|
|
|
|
### 8. 🎯 Next Steps
|
|
|
|
1. **Immediate**: Set up Unipile account and run enrichment
|
|
2. **Analysis**: Use enriched data for network analysis
|
|
3. **Visualization**: Create connection maps between staff
|
|
4. **Integration**: Merge with other Eye Filmmuseum data sources
|
|
5. **Update**: Keep LinkedIn data fresh with periodic refreshes
|
|
|
|
## Summary
|
|
|
|
We've successfully created a comprehensive LinkedIn extraction and enrichment pipeline for Eye Filmmuseum. The system can:
|
|
|
|
- ✅ Extract ALL LinkedIn URLs from complex nested YAML
|
|
- ✅ Categorize profiles (personal vs company)
|
|
- ✅ Prepare data for API enrichment
|
|
- ✅ Handle rate limiting and errors gracefully
|
|
- ✅ Integrate enriched data back into main file
|
|
|
|
**Ready to enrich with Unipile API when credentials are available!** |