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Content Analysis Sentiment API

Name: Content Analysis Sentiment API
Brand: SocialCrawl
Availability: InStock

Scrape Content Analysis Sentiment data with one API call. Returns two sentiment distributions for the keyword's web mentions: a positive/negative/neutral split (each a full summary sub-object) and a 6-axis emotional split (anger, happiness, love, sadness, share, fun — each a full summary sub-object). Sentiment is DataForSEO's model-derived NLP, passed through verbatim — not ground truth.

Last updated July 2026Maintained by the SocialCrawl team

Start for free View Documentation

Searching 44 platforms in parallel

TikTok·

Instagram·

YouTube·

Facebook·

X·

LinkedIn·

Reddit·

Threads·

Pinterest·

Twitch·

Truth Social·

Snapchat·

Kick·

Bluesky·

Kwai·

Rumble·

Spotify·

TikTok Shop·

Amazon Shop·

Google Shopping·

Trustpilot·

TripAdvisor·

Linktree·

Komi·

Pillar·

lnk.bio·

Facebook Ads·

Google Ads·

LinkedIn Ads·

Google Search·

Google News·

Google Finance·

Polymarket·

Tavily·

Hacker News·

GitHub·

Perplexity·

Naver·Utility·

Universal Search

TikTok·

Instagram·

YouTube·

Facebook·

X·

LinkedIn·

Reddit·

Threads·

Pinterest·

Twitch·

Truth Social·

Snapchat·

Kick·

Bluesky·

Kwai·

Rumble·

Spotify·

TikTok Shop·

Amazon Shop·

Google Shopping·

Trustpilot·

TripAdvisor·

Linktree·

Komi·

Pillar·

lnk.bio·

Facebook Ads·

Google Ads·

LinkedIn Ads·

Google Search·

Google News·

Google Finance·

Polymarket·

Tavily·

Hacker News·

GitHub·

Perplexity·

Naver·Utility·

Universal Search

TikTok·

Instagram·

YouTube·

Facebook·

X·

LinkedIn·

Reddit·

Threads·

Pinterest·

Twitch·

Truth Social·

Snapchat·

Kick·

Bluesky·

Kwai·

Rumble·

Spotify·

TikTok Shop·

Amazon Shop·

Google Shopping·

Trustpilot·

TripAdvisor·

Linktree·

Komi·

Pillar·

lnk.bio·

Facebook Ads·

Google Ads·

LinkedIn Ads·

Google Search·

Google News·

Google Finance·

Polymarket·

Tavily·

Hacker News·

GitHub·

Perplexity·

Naver·Utility·

Universal Search

TikTok·

Instagram·

YouTube·

Facebook·

X·

LinkedIn·

Reddit·

Threads·

Pinterest·

Twitch·

Truth Social·

Snapchat·

Kick·

Bluesky·

Kwai·

Rumble·

Spotify·

TikTok Shop·

Amazon Shop·

Google Shopping·

Trustpilot·

TripAdvisor·

Linktree·

Komi·

Pillar·

lnk.bio·

Facebook Ads·

Google Ads·

LinkedIn Ads·

Google Search·

Google News·

Google Finance·

Polymarket·

Tavily·

Hacker News·

GitHub·

Perplexity·

Naver·Utility·

Universal Search

Content Analysis API

What can you do with the Sentiment API?

The Sentiment endpoint gives you structured Content Analysis data with computed fields in a single request. No scraping infrastructure to build or maintain.

Example Request

curl -H "x-api-key: YOUR_API_KEY" \
  "https://www.socialcrawl.dev/v1/content_analysis/sentiment?keyword=openai"

import requests

response = requests.get(
    "https://www.socialcrawl.dev/v1/content_analysis/sentiment",
    params={
    'keyword': 'openai',
    },
    headers={"x-api-key": "YOUR_API_KEY"},
)

data = response.json()

const response = await fetch(
  "https://www.socialcrawl.dev/v1/content_analysis/sentiment?keyword=openai",
  {
    headers: { "x-api-key": "YOUR_API_KEY" },
  },
);

const data = await response.json();

Parameters

Parameter	Required	Description
keyword	Yes	Brand or term to analyze.
page_type	No	Narrow to one or more page types (comma-separated): ecommerce, news, blogs, message-boards, organization. (ecommerce \| news \| blogs \| message-boards \| organization)
positive_connotation_threshold	No	Minimum positive-connotation probability (0–1, default 0.4).
filters	No	Advanced DataForSEO filter expression as a JSON array (≤8 conditions).

Example Response

What does the Content Analysis Sentiment API return?

Every response follows one unified schema. Here is a real, unmodified response body, so you can see the exact fields you get back before spending a credit.

Example response

{
  "success": true,
  "platform": "instagram",
  "endpoint": "/v1/instagram/engagement",
  "data": {
    "engagement_rate_percentages": 38.33,
    "recent_posts": 12,
    "followers": 87608035,
    "comments": 528912,
    "likes": 33049046,
    "recent_posts_explanation": "Statistics based on the last 12 posts",
    "id_user": "2278169415",
    "username": "mrbeast",
    "is_private": false,
    "posts_details": [
      {
        "likes": 5636982,
        "comments": 69484,
        "taken_at": 1781457954,
        "datetime": "2026-06-14 20:25:54",
        "hours_since_post": 461,
        "time_ago": "19 days ago",
        "likes_per_hour": 12228,
        "comments_per_hour": 151
      },
      {
        "likes": 20000768,
        "comments": 223510,
        "taken_at": 1732824650,
        "datetime": "2024-11-28 23:10:50",
        "hours_since_post": 13971,
        "time_ago": "2 years ago",
        "likes_per_hour": 1432,
        "comments_per_hour": 16
      },
      {
        "likes": 929226,
        "comments": 30633,
        "taken_at": 1782232475,
        "datetime": "2026-06-23 19:34:35",
        "hours_since_post": 246,
        "time_ago": "10 days ago",
        "likes_per_hour": 3777,
        "comments_per_hour": 125
      },
      {
        "likes": 487761,
        "comments": 22482,
        "taken_at": 1781799425,
        "datetime": "2026-06-18 19:17:05",
        "hours_since_post": 366,
        "time_ago": "15 days ago",
        "likes_per_hour": 1333,
        "comments_per_hour": 61
      },
      {
        "likes": 712265,
        "comments": 15716,
        "taken_at": 1781366405,
        "datetime": "2026-06-13 19:00:05",
        "hours_since_post": 487,
        "time_ago": "20 days ago",
        "likes_per_hour": 1463,
        "comments_per_hour": 32
      },
      {
        "likes": 1475116,
        "comments": 35386,
        "taken_at": 1781277094,
        "datetime": "2026-06-12 18:11:34",
        "hours_since_post": 512,
        "time_ago": "21 days ago",
        "likes_per_hour": 2881,
        "comments_per_hour": 69
      },
      {
        "likes": 1108220,
        "comments": 26632,
        "taken_at": 1780160249,
        "datetime": "2026-05-30 19:57:29",
        "hours_since_post": 822,
        "time_ago": "1 months ago",
        "likes_per_hour": 1348,
        "comments_per_hour": 32
      },
      {
        "likes": 542948,
        "comments": 28476,
        "taken_at": 1779375582,
        "datetime": "2026-05-21 17:59:42",
        "hours_since_post": 1040,
        "time_ago": "1 months ago",
        "likes_per_hour": 522,
        "comments_per_hour": 27
      },
      {
        "likes": 698514,
        "comments": 24401,
        "taken_at": 1779120014,
        "datetime": "2026-05-18 19:00:14",
        "hours_since_post": 1111,
        "time_ago": "2 months ago",
        "likes_per_hour": 629,
        "comments_per_hour": 22
      },
      {
        "likes": 468000,
        "comments": 13548,
        "taken_at": 1778947209,
        "datetime": "2026-05-16 19:00:09",
        "hours_since_post": 1159,
        "time_ago": "2 months ago",
        "likes_per_hour": 404,
        "comments_per_hour": 12
      },
      {
        "likes": 526594,
        "comments": 24411,
        "taken_at": 1777737719,
        "datetime": "2026-05-02 19:01:59",
        "hours_since_post": 1495,
        "time_ago": "2 months ago",
        "likes_per_hour": 352,
        "comments_per_hour": 16
      },
      {
        "likes": 462652,
        "comments": 14233,
        "taken_at": 1777580305,
        "datetime": "2026-04-30 23:18:25",
        "hours_since_post": 1538,
        "time_ago": "2 months ago",
        "likes_per_hour": 301,
        "comments_per_hour": 9
      }
    ]
  },
  "credits_used": 5,
  "credits_remaining": 9999,
  "request_id": "req_example000000",
  "cached": false
}

Example captured from the Instagram API. Every SocialCrawl endpoint returns this same unified schema, so your Content Analysis Sentiment response has the same fields.

API Details

How does the Content Analysis Sentiment API work?

Send a GET request with your API key and get back clean, structured JSON in our unified schema. Supported computed fields are populated when the source provides the required inputs.

Method

GET

Response

JSON

Why SocialCrawl

Why use SocialCrawl for Content Analysis Sentiment data?

We handle the complexity of Content Analysis data extraction so you can focus on building. Unified schema, AI enrichment, and zero platform logic in your code.

One schema for every platform — write your integration once
When an endpoint supports a computed field and the required source inputs are available, normalized records can include fields such as engagement rate, reach, category, and language
No scraping infrastructure to build, no proxies to manage, no rate limits to fight
Current public Content Analysis data, with the endpoint's documented cache window and 0-credit hits; send Cache-Control: no-cache for a billed refresh

Developer First

How do you scrape social media data in seconds?

The fastest social media scraping API for developers. Scrape profiles, posts, comments, and analytics from 44 platforms covering 10B+ monthly active users.

One schema, every platform

Query 44 platforms with identical response structures. Write your integration once.

Computed fields, not just scraped

When an endpoint supports these metrics and the source provides the required inputs, the normalized record includes engagement_rate, estimated_reach, content_category, and language — ready to use.

See your data before you code

Visual Data Explorer — paste any URL, get rich result cards, sortable tables, CSV export.

import requests

response = requests.get(
    'https://www.socialcrawl.dev/v1/tiktok/profile',
    params={'handle': 'charlidamelio'},
    headers={'x-api-key': 'sc_YOUR_API_KEY'}
)
data = response.json()

[ .JSON ]

{
  "success": true,
  "platform": "tiktok",
  "data": {
    "author": {
      "username": "charlidamelio",
      "followers": 152400000
    },
    "engagement": {
      "likes": 12400000000,
      "engagement_rate": 0.087
    },
    "metadata": {
      "language": "en",
      "content_category": "lifestyle"
    }
  }
}

+ 44 platforms

FAQ

Have a question? We got answers

Find answers to frequently asked questions about SocialCrawl's API, pricing, and capabilities.

How do I run sentiment analysis on brand mentions?

Send a GET request to /v1/content_analysis/sentiment with the keyword parameter. You get two distributions back: the positive/negative/neutral connotation split and the 6-axis emotion split (anger, happiness, love, sadness, share, fun), each as a full summary sub-object.

Is the sentiment ground truth or model output?

It is model-derived NLP, not ground truth. The sentiment analysis API returns the probabilities the model assigned across web mentions of your keyword. SocialCrawl passes those values through verbatim, so apply your own confidence thresholds before acting on them.

What is the 6-axis emotion model?

Beyond the positive/negative/neutral split, each mention is scored on six emotional axes — anger, happiness, love, sadness, share, and fun. The sentiment endpoint aggregates those into a distribution so you can see which emotions dominate the conversation around a term.

How is sentiment different from the summary endpoint?

Summary gives you mention totals, top domains, categories, and breakdowns plus sentiment totals. The sentiment endpoint focuses purely on the two distributions — connotation and 6-axis emotion — when emotional makeup is what you care about, not volume or sources.

How much does the sentiment analysis API cost?

Each sentiment request costs 5 credits on the advanced tier. New accounts get 100 free credits with no credit card required, so you can compare the emotional profile of several brands or terms before you pay anything.

Ask AI about SocialCrawl

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