DopamineDesk News Sentiment API

x402

DopamineDesk News Sentiment API is a paid API for AI agents from ai-data-marketplace-1042299154756.us-central1.run.app, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-13).

Returns a sentiment score, label, and top articles for a named company, brand, or person based on recent news coverage.

Price / call$0.05

Seller volume →—

Success—

StatusUnknown

How this service works

Fetch recent Hacker News stories for a topic and apply a transparent keyword-lexicon sentiment score.

Output

A JSON object containing the entity name, an overall sentiment score (0–1 float), a human-readable sentiment label (e.g. 'Bullish/Positive'), a count of articles analyzed, and an array of top articles each with title, source, and individual sentiment score.

Example use cases

Pre-investment due diligence check

“Before I buy shares in Nvidia, can you pull the news sentiment for the past 30 days and tell me if coverage is mostly positive or negative, with the top articles?”

Brand reputation monitoring

“What does the news sentiment look like for Nike right now? I want to know if recent press is positive or negative and see which stories are getting the most coverage.”

Competitive intelligence snapshot

“Run a news sentiment check on Apple and tell me the overall score, whether it's bullish or bearish, and how many articles came up in the last 14 days.”

Technical details

Endpoint

GEThttps://ai-data-marketplace-1042299154756.us-central1.run.app/api/v1/news_sentiment

When to prefer

Choose this endpoint when you need a quick, quantified news sentiment signal for a specific company, brand, or public figure — especially for pre-investment research, brand health checks, or competitive intelligence. It is best when you want both a numeric score and labeled sentiment backed by real article references, rather than raw social media sentiment or stock price data.

Side effects

Missing or unrecognized entity name returns an error or empty results
Lookback period too long may return limited data if news coverage is sparse
Rate limits or payment failures return 402 or 429 errors
Ambiguous entity names (e.g. common words) may return mixed or inaccurate results
No recent news coverage for the entity may yield low article count and unreliable sentiment

Input

Schema · Request body

Field	Type	Description
inputrequired	object
output	object

Output

Schema · Response

{
  "type": "json",
  "example": {
    "topic": "Microsoft",
    "source": "Hacker News Algolia API",
    "success": true,
    "articles": [
      "[nested detail omitted from the challenge header; see the full example in /openapi.json]"
    ],
    "fetched_at": "2026-08-07T07:32:38.571Z",
    "analysis_method": "transparent keyword-lexicon sentiment v1",
    "sentiment_label": "NEUTRAL",
    "sentiment_score": 0,
    "articles_analyzed": 10,
    "marketplace_metadata": {
      "source": "Hacker News Algolia API plus deterministic lexicon",
      "billable": true,
      "data_mode": "live_source",
      "availability": "operational"
    }
  }
}

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How this service works

Fetch recent Hacker News stories for a topic and apply a transparent keyword-lexicon sentiment score.

Output

Example use cases

Pre-investment due diligence check

“Before I buy shares in Nvidia, can you pull the news sentiment for the past 30 days and tell me if coverage is mostly positive or negative, with the top articles?”

Brand reputation monitoring

“What does the news sentiment look like for Nike right now? I want to know if recent press is positive or negative and see which stories are getting the most coverage.”

Competitive intelligence snapshot

“Run a news sentiment check on Apple and tell me the overall score, whether it's bullish or bearish, and how many articles came up in the last 14 days.”

Technical details

Endpoint

GEThttps://ai-data-marketplace-1042299154756.us-central1.run.app/api/v1/news_sentiment

When to prefer

Side effects

Missing or unrecognized entity name returns an error or empty results
Lookback period too long may return limited data if news coverage is sparse
Rate limits or payment failures return 402 or 429 errors
Ambiguous entity names (e.g. common words) may return mixed or inaccurate results
No recent news coverage for the entity may yield low article count and unreliable sentiment

Input

Schema · Request body

Field	Type	Description
inputrequired	object
output	object

Output

Schema · Response

{
  "type": "json",
  "example": {
    "topic": "Microsoft",
    "source": "Hacker News Algolia API",
    "success": true,
    "articles": [
      "[nested detail omitted from the challenge header; see the full example in /openapi.json]"
    ],
    "fetched_at": "2026-08-07T07:32:38.571Z",
    "analysis_method": "transparent keyword-lexicon sentiment v1",
    "sentiment_label": "NEUTRAL",
    "sentiment_score": 0,
    "articles_analyzed": 10,
    "marketplace_metadata": {
      "source": "Hacker News Algolia API plus deterministic lexicon",
      "billable": true,
      "data_mode": "live_source",
      "availability": "operational"
    }
  }
}