Data Dictionary: Employee Posts API

Overview

Data dictionary for data retrieved using Employee Posts API endpoints.

This data dictionary shows all available data points, explains their values, and provides data samples from the API Employee Posts dataset.

Data points per category

1. Author

2. Post information

3. Comments

All personal/company information mentioned within this context is entirely fictional and is solely intended for illustrative purposes.

Author

Data point	Description	Data type
author_name	Employee's full name	String
author_profile_url	Employee's profile URL	String
author_headline	Headline or title of the author (if available)	String
author_posts_count	Number of all author's posts	Integer

Refer to the table example from the data:

Author

"author_name": "John Doe",
"author_profile_url": "https://professional-network.com/in/john-doe",
"author_headline": "Data Analyst @Company Example | Data is my passion",
"author_posts_count": 100,

Post information

Data point	Description	Data type
id	Post's ID	String
url	Post's URL	String
date_published	Post publication date	String
article_body	Content of the post	String
image_url	URL of an image attached to the post (if available)	String
hashtags	List of hashtags used in the post	Array
mentions	Mentions of other profiles	Array of strings
full_name	Mention within the post	String
url	Profile URL of the mentioned entity	String
reaction_count	Number of reactions (likes, claps, etc.) on the post	Integer

Refer to the table example from the data:

Post information

"id": "1234567890123456",
"url": "https://www.professional-network.com/posts/johndoe_example-post-123456",
"date_published": "2025-07-01",
"article_body": "Data is only as valuable as the insights you can draw from it, and the right structure makes all the difference. With Jane Doe, we're building tools that turn raw data into clear, actionable stories.",
"image_url": "https://example.com/image/link123456789",
"hashtags": [
        "#Data",
        "#Inspiring"
    ],
"mentions": [
    {
        "full_name": "Jane Doe",
        "url": "https://professional-network.com/in/jane-doe"
    }
],
"reaction_count": 10,

Comments

Data point	Description	Data type
comment_count	Number of comments on the post	Integer
comments	List of comments on the post	Array of objects
full_name	Name of the person who made the comment	String
headline	Headline or title of the commenter (if available)	String
profile_url	URL of the commenter’s profile	String
body	Content of the comment	String
reaction_count	Number of reactions on the comment	Integer
date_published	Time when comment was published	String

Refer to the table example from the data:

Comments

"comment_count": 2,
"comments": [
   {
      "full_name": "John Smith",
      "headline": "Talent Intelligence@ Example corp | Meta Alumni",
      "profile_url": "https://www.professional-network.com/in/john-smith",
      "body": "Great opportunity",
      "reaction_count": 1,
      "date_published": "2025-07-01"
   },
   {
      "full_name": "Jane Smith",
      "headline": "Looking for a job in QA | Functional Testing ",
      "profile_url": "https://professional-network.com/in/jane-smith",
      "body": "I'd be interested to join your team",
      "reaction_count": 0,
      "date_published": "2025-07-02"
   }
]