The Vetric Instagram Post Comments allows you to get the comments from a Instagram post.

The complete Vetric documentation about their endpoint can be found in their site here.

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Unify Schema
This data source already use Unify Schema.

API Key

To use this component, you will need a Vetric API key. If you don't have one, please reach out to [email protected] and our team will assist you in obtaining the necessary credentials.

How To Use?

The component is powered by the Jobs System, when interacting with the component you have the option to define your jobs queries.

Search Query

Filters

Filter Name	Description
query	Instagram post ID
query_from	Filter dates from/since - Example '2024-05-01T00:00:00Z'
query_to	Filter dates to - Example '2024-08-01T00:00:00Z'
max_documents	Set a limit for the number of documents that will be fetched for the search.
max_excess_documents	When filtering by date, this sets the limit of documents to process that fall outside the date range. This serves as a cost-control measure. Note that costs apply for all retrieved documents, including those that are discarded.

Since the Vetric endpoint does not natively support date filtering, the query_from and query_to filters are applied in memory. Because we cannot guarantee how many documents must be retrieved to find those within the desired date range, the max_excess_documents field can be used to limit the number of documents processed.

Examples

Retrieve the comments from the Instagram post with ID '2872992039991068281'.

You also have the option to use the API. You can use the Code button to extract this example:

curl --location 'https://api.platform.datastreamer.io/api/pipelines/{PIPELINE_ID}/components/{COMPONENT_ID}/jobs?ready=true' \
      --header 'apikey: <your-api-key>' \
      --header 'Content-Type: application/json' \
      --data \
        '{
          "job_name": "4ccf025f-e57c-4d64-801d-1127dcf5fd16",
          "component_name": "vetric-instagram-post-comments-ingress",
          "data_source": "vetric_instagram_post_comments",
          "query": {
            "query": "2872992039991068281",
            "max_excess_documents": 200
          },
          "job_type": "oneTime",
          "query_from": "2025-12-01T00:00:00.000Z",
          "query_to": "2025-12-18T00:00:00.000Z",
          "max_documents": 10
        }'

For more details on creating data collection jobs, see Job Management.

Additional Details

Compatible Metadata Fields

Applicable Metadata Categories	Compatible
Source	Yes
Content	Yes
Author	Yes
Person	No
Enrichment	Yes
Organization	No
Data source-specific fields?	Yes, please see the Metadata page.

Metadata Example

{
  "data_source": "vetric_instagram_post_comments",
  "id": "18028783430313694",
  "author": {
    "userid": "10433902",
    "handle": "witchymanny",
    "name": "Manny Santiago",
    "profile_image_source": "https://scontent-mia3-2.cdninstagram.com/v/t51.2885-19/412681983_737915625035107_2553032032391286942_n.jpg?stp=dst-jpg_e0_s150x150&_nc_ht=scontent-mia3-2.cdninstagram.com&_nc_cat=107&_nc_ohc=jojHwMEWYAsQ7kNvgHEIsSB&_nc_gid=16201b5b268e40a8b98f0678031cb6fc&edm=AId3EpQBAAAA&ccb=7-5&oh=00_AYC1ZAYF0cWweWFYrAcVCjxpOMIcPh4BMEwIOEB7psvwcw&oe=66D826AE&_nc_sid=f5838a",
    "verified": false,
    "is_mentionable": true,
    "url": "https://www.instagram.com/witchymanny"
  },
  "doc_date": "2024-05-23T23:44:26.000Z",
  "content": {
    "published": "2024-05-23T23:44:26.000Z",
    "body": "See you tonight!!!",
    "likes_count": 15,
    "child_comments_count": 1,
    "related_post_id": "3374401724196409143"
  },
  "instagram": {
    "content_type": "comment"
  }
}

Data collection job creation request

Returns comments on an Instagram post. The query value is expected to be a valid Instagram Post Id.

curl --location 'https://api.platform.datastreamer.io/api/pipelines/{PIPELINE_ID}/components/{COMPONENT_ID}/jobs?ready=true' \
      --header 'apikey: <your-api-key>' \
      --header 'Content-Type: application/json' \
      --data \
        '{
			    "job_name": "my instagram data collection",
			    "data_source": "vetric_instagram_post_comments",
			    "query": {
			            "query": "3374401724196409143"
			        },
			    "job_type": "oneTime"
				}'

Make sure to replace ‘PIPELINE_ID’ and ‘COMPONENT_ID’ variables to the ones associated with your pipeline.

Including Post Comments from Other Sources

The vetric_instagram_post_comments connector can be used in conjunction with other connectors like vetric_instagram_user_reels and vetric_instagram_user_feed to include comments for the Instagram User Reel or Feed posts you collect. By specifying the include option in your query, you can retrieve comments associated with each post, providing a more comprehensive view of user interactions.

For more details, refer to the documentation for Instagram User Reels and Instagram User Feed.