What are tags?
Tags hold additional information about a person and their attributes. Examples of tags associated with a given person include:
- Information about a their holdings such as auto models (auto make, VIN)
- Skills and interests
- Domains they own
- Number of Twitter followers / users they follow
Tags returned in the Pipl API response contain data that do not fit into the person object model. Tags are classified based on the type of information they contain, and the content may be unstructured free text.
How to Enable Tags
Tags may appear in individual source objects in the source array. To see tags in the response, make sure that the sources layer is enabled by using the show_sources parameter in the search request (with the relevant value for your use case).
NOTE
You can't use tags as input into search queries, or with the match requirement field.
Popular tag classifications
Use the following table to assist you in discovering popular tag classifications.
Tag Data | Source Name(s) | Tag classification(s) | Sample value(s) |
|---|---|---|---|
Professional credentials and accomplishments | skill, course, group, volunteering |
| |
Social media follower and following count | Twitter, Instagram, Pinterest, Tiktok, Soundcloud, Github, Vimeo, VK, Foursquare, Academia, Medium, Strava | following, followers |
|
Vehicle information | Auto Owner* | auto year, auto make, auto model, auto vin |
|
Website ownership information | Domain Owner* | associated domain |
|
Death information | Deceased Residents, FindAGrave | death date, deceased, burial address |
|
Home ownership information | Residential Property, Trust Property | last_sale_date, apn, type |
|
NPI (National Provider Identifier) | NPPES NPI Registry | nppes_npi_license |
|
NOTE
* For certain sources, the source name may not be exactly as specified in the table above, but may be similarly named. Check that the string contains the content, and do a case insensitive comparison.
Example
This example illustrates how tags may appear in a source object in the sources array. This includes different classifications of tags such as skill, group and auto make.
"sources": [
{
"@id": "4275e03c9c99953245c426dd74cd61c5",
"@category": "professional_and_business",
"@name": "LinkedIn",
"@origin_url": "http://www.linkedin.com/in/theman",
"@domain": "linkedin.com",
"@person_id": "a0f13c3c-bcd9-4133-979c-9f2ba05decf8",
"@match": 1.0,
"names": [....
],
"usernames": [....
],
"tags": [
{
"@valid_since": "2015-09-01",
"@last_seen": "2016-08-26",
"@classification": "skill",
"content": "Microsoft Office"
},
{
"@valid_since": "2015-09-01",
"@last_seen": "2016-08-26",
"@classification": "skill",
"content": "Python"
},
{
"@valid_since": "2015-09-01",
"@last_seen": "2016-08-26",
"@classification": "group",
"content": "Python developers unite"
},
{
"@valid_since": "2016-01-22",
"@last_seen": "2016-08-26",
"@classification": "volunteering",
"content": "Chef at Home for the Homeless"
},
{
"@valid_since": "2016-07-22",
"@last_seen": "2016-08-26",
"@classification": "course",
"content": "Python for pros"
},
{
"@valid_since": "2017-06-01",
"@last_seen": "2017-06-01",
"@classification": "auto make",
"content": "FORD"
},
{
"@valid_since": "2017-06-01",
"@last_seen": "2017-06-01",
"@classification": "auto model",
"content": "MONDEO"
},
{
"@valid_since": "2017-06-01",
"@last_seen": "2017-06-01",
"@classification": "auto vin",
"content": "1ABC21Z39EF90123"
}
]