Proportion of Ads by Industry Segment
We want to get a by industry segment understanding of features and relationships between features in our online commercial sex data at the ad-level. Currently, features that are especially relevant to our industry segment vetting process are prioritized. Current analyses rely on a sample of online CS ads that were manually vetted to determine segment type. Further, select features were manually annotated (i.e., price, race, hispanic status, etc.). That said, the current analysis relies on a hybrid of automatically generated feature values and manually annotated feature values.
| Segment | Prop. Min Age |
|---|---|
| escort_services | 7.16% |
| pic_vid_sales | 7.07% |
| brothel_residence | 6.25% |
| all ads | 5.67% |
| outdoor_solicitation | 4.12% |
| stripclub_bar_casino | 2.90% |
| Segment | Mean Price | Median Price | Mode Price |
|---|---|---|---|
| pic_vid_sales | 237 | 250 | 300 |
| outdoor_solicitation | 232 | 250 | 300 |
| stripclub_bar_casino | 230 | 180 | 150 |
| all ads | 165 | 150 | 300 |
| escort_services | 162 | 150 | 300 |
| brothel_residence | 151 | 160 | 160 |
| massage_parlor | 75 | 60 | 60 |
| Segment | Mean Overnight Price | Median Overnight Price | Mode Overnight Price |
|---|---|---|---|
| stripclub_bar_casino | 1500 | 1500 | 1500 |
| pic_vid_sales | 1021 | 800 | 800 |
| outdoor_solicitation | 887 | 1000 | 1000 |
| all ads | 882 | 800 | 1500 |
| escort_services | 857 | 225 | 1500 |
| massage_parlor | 100 | 100 | 100 |
