News Sentiment Analyzer
Pricing
$6.50 / 1,000 article analyzeds
Go to Apify Store
News Sentiment Analyzer
Analyze news articles for sentiment using NLP. Extract positive, negative, and neutral signals from any news URL or keyword-based news feed.
News Sentiment Analyzer
Pricing
$6.50 / 1,000 article analyzeds
Analyze news articles for sentiment using NLP. Extract positive, negative, and neutral signals from any news URL or keyword-based news feed.
You can access the News Sentiment Analyzer programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "1.0", "x-build-id": "hEi2QtA4rKNqBzXaU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/junipr~news-sentiment-analyzer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-junipr-news-sentiment-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/junipr~news-sentiment-analyzer/runs": { "post": { "operationId": "runs-sync-junipr-news-sentiment-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/junipr~news-sentiment-analyzer/run-sync": { "post": { "operationId": "run-sync-junipr-news-sentiment-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "query": { "title": "Search Query", "type": "string", "description": "Search query — company name, ticker symbol, topic, or keyword phrase. Leave empty to use 'queries' array instead.", "default": "technology news" }, "queries": { "title": "Multiple Queries", "type": "array", "description": "Run multiple queries in a single actor run. Each query gets its own sentiment summary. If both 'query' and 'queries' are provided, 'query' is prepended to the list.", "items": { "type": "string" } }, "sources": { "title": "News Sources", "type": "array", "description": "Which news sources to scrape. Google News and Bing News provide the broadest coverage for most queries.", "items": { "type": "string" }, "default": [ "google_news", "bing_news" ] }, "maxArticlesPerQuery": { "title": "Max Articles Per Query", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of articles to scrape and analyze per query. Higher values give more data but take longer to run.", "default": 50 }, "language": { "title": "Language", "type": "string", "description": "Language code for news results (ISO 639-1). Used to filter news to a specific language.", "default": "en" }, "country": { "title": "Country", "type": "string", "description": "Country code for regional news results (ISO 3166-1 alpha-2). Affects which regional news appears in results.", "default": "US" }, "dateRange": { "title": "Date Range", "enum": [ "1d", "3d", "7d", "14d", "30d", "90d" ], "type": "string", "description": "How far back to look for articles. Shorter ranges give more current sentiment; longer ranges show trends.", "default": "7d" }, "sentimentModel": { "title": "Sentiment Model", "enum": [ "afinn", "pattern" ], "type": "string", "description": "Sentiment analysis model to use. 'afinn' is faster (word-level scoring). 'pattern' is slower but considers sentence structure.", "default": "afinn" }, "extractEntities": { "title": "Extract Named Entities", "type": "boolean", "description": "Extract named entities (people, companies, locations) from articles and include per-entity sentiment scores.", "default": true }, "extractTopics": { "title": "Extract Topics", "type": "boolean", "description": "Extract and cluster key topics and themes across articles. Useful for identifying what's driving sentiment.", "default": true }, "includeArticleText": { "title": "Include Full Article Text", "type": "boolean", "description": "Include the full extracted article text in each output item. Increases dataset size significantly — only enable if you need the raw text.", "default": false }, "minArticleLength": { "title": "Minimum Article Length", "minimum": 0, "maximum": 5000, "type": "integer", "description": "Minimum character length for an article to be analyzed. Articles shorter than this are saved to the dataset with a ARTICLE_TOO_SHORT error and no sentiment score.", "default": 100 }, "groupBySource": { "title": "Group By Source", "type": "boolean", "description": "Include a per-source sentiment breakdown in the run summary (stored in the Key-Value Store as OUTPUT).", "default": true }, "groupByDate": { "title": "Group By Date", "type": "boolean", "description": "Include a daily sentiment time-series in the run summary. Shows how sentiment is trending over time.", "default": true }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for scraping news sources. Datacenter proxy is sufficient for most news sites.", "default": { "useApifyProxy": true } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for News Sentiment Analyzer from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: