Twitter Tweet Comments

Get the comments (replies) on a specific tweet. Returns the full content and engagement metrics for each reply. Supports pagination.

Endpoint

GET /v1/twitter/tweet/comments

Price: $0.006 per page Free tier: 50 requests/month

Parameters

Parameter	Required	Description
`tweet_id`	Yes	Numeric tweet ID
`pages`	No	Number of pages to fetch, 1-10 (default: 1)
`get_sentiment`	No	Set to `true` to add AI emotion analysis (Plutchik’s Wheel) to each result. Adds +$0.001 per page to the cost. Returns emotion scores, dominant emotion, intensity, and polarity.

Response Fields

Field	Type	Description
`comments`	array	Array of reply tweets
`comments[].title`	string	Tweet title (format: `@username on X`)
`comments[].url`	string	Direct link to the reply
`comments[].date`	string	Publication date and time
`comments[].author`	string	Twitter username of the commenter
`comments[].source`	string	`"Twitter (X)"`
`comments[].domain`	string	`"x.com"`
`comments[].snippet`	string	Reply content text
`comments[].likes`	integer	Number of likes
`comments[].retweets`	integer	Number of retweets
`comments[].replies`	integer	Number of replies to this comment
`comments[].quotes`	integer	Number of quote tweets
`comments[].bookmarks`	integer	Number of bookmarks
`comments[].views`	integer/null	Number of views
`comments[].author_followers`	integer	Commenter’s follower count
`comments[].author_verified`	boolean	Whether the commenter is verified
`comments[].lang`	string	Tweet language code
`comments[].is_reply`	boolean	Always `true` for this endpoint
`comments[].is_quote`	boolean	Whether the reply is also a quote
`comments[].hashtags`	string[]	Hashtags used
`comments[].user_mentions`	string[]	Usernames mentioned
`comments[].sentiment`	object/null	Emotion analysis results. Only present when `get_sentiment=true`. Returns `null` if analysis fails.
`comments[].sentiment.emotions`	object	Plutchik emotion scores (0-100) for: `joy`, `trust`, `fear`, `surprise`, `sadness`, `disgust`, `anger`, `anticipation`.
`comments[].sentiment.dominant_emotion`	string	The emotion with the highest score.
`comments[].sentiment.emotional_intensity`	integer	Overall emotional intensity on a scale of 0-10.
`comments[].sentiment.polarity`	string	Overall sentiment polarity: `positive`, `negative`, or `neutral`.
`tweet_id`	string	Requested tweet ID
`pages`	integer	Number of pages fetched
`count`	integer	Total results returned

Example Request

cURL

curl "https://apidirect.io/v1/twitter/tweet/comments?tweet_id=1631781099415257088&pages=1" \
  -H "X-API-Key: YOUR_API_KEY"

Python

import requests

response = requests.get(
    "https://apidirect.io/v1/twitter/tweet/comments",
    headers={"X-API-Key": "YOUR_API_KEY"},
    params={"tweet_id": "1631781099415257088", "pages": 1}
)
print(response.json())

Example Response

{
  "comments": [
    {
      "title": "@commenter on X",
      "url": "https://twitter.com/commenter/status/...",
      "date": "2024-01-15 15:00:00",
      "author": "commenter",
      "source": "Twitter (X)",
      "domain": "x.com",
      "snippet": "@username Great post! Totally agree.",
      "likes": 50,
      "retweets": 5,
      "replies": 2,
      "quotes": 0,
      "bookmarks": 3,
      "views": 5000,
      "author_followers": 2500,
      "author_verified": false,
      "lang": "en",
      "is_reply": true,
      "is_quote": false,
      "hashtags": [],
      "user_mentions": ["username"],
      "sentiment": {
        "emotions": {
          "joy": 40,
          "trust": 55,
          "fear": 0,
          "surprise": 10,
          "sadness": 0,
          "disgust": 0,
          "anger": 0,
          "anticipation": 30
        },
        "dominant_emotion": "trust",
        "emotional_intensity": 5,
        "polarity": "positive"
      }
    }
  ],
  "tweet_id": "1631781099415257088",
  "pages": 1,
  "count": 20
}