Social Media Sentiment Analysis Tool
Pricing
$1.50 / 1,000 comments
Go to Store
Social Media Sentiment Analysis Tool
Add a profile name and find this social profile on Facebook, Instagram, and TikTok, scrape its recent posts and comments, and perform sentiment analysis for each comment. All in one go. Export results in JSON, CSV, HTML, use API, schedule runs, integrate with other tools.
4.2 (7)
Pricing
$1.50 / 1,000 comments
41
Total users
820
Monthly users
153
Runs succeeded
57%
Issues response
7.2 days
Last modified
24 days ago
You can access the Social Media Sentiment Analysis Tool programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, youāll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.0", "x-build-id": "jH3qguSazlYDcRohv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/tri_angle~social-media-sentiment-analysis-tool/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-tri_angle-social-media-sentiment-analysis-tool", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/tri_angle~social-media-sentiment-analysis-tool/runs": { "post": { "operationId": "runs-sync-tri_angle-social-media-sentiment-analysis-tool", "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/tri_angle~social-media-sentiment-analysis-tool/run-sync": { "post": { "operationId": "run-sync-tri_angle-social-media-sentiment-analysis-tool", "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": { "facebookProfileName": { "title": "Facebook profile", "type": "string", "description": "Profile identifier from the Facebook profile url (e.g. \"arnold\")" }, "instagramProfileName": { "title": "Instagram profile", "type": "string", "description": "Profile identifier from the Instagram profile url (e.g. \"schwarzenegger\")" }, "tiktokProfileName": { "title": "TikTok profile", "type": "string", "description": "Profile identifier from the TikTok profile url (e.g. \"arnoldschnitzel\")" }, "sentimentAnalysis": { "title": "Sentiment Analysis for comments", "type": "boolean", "description": "If checked the comments in Dataset will include information about their sentiment score", "default": true }, "latestPosts": { "title": "Latest posts", "type": "integer", "description": "Amount of latest posts scraped per each social profile", "default": 10 }, "latestComments": { "title": "Latest comments", "type": "integer", "description": "Amount of latest comments scraped per each post", "default": 50 }, "profileName": { "title": "Unspecific profile name", "type": "string", "description": "Based on this input the profile name will be determined by the search engine (use if you don't know the exactl profile name exactly - e.g. Arnold Schwarzenegger)" }, "scrapeFacebook": { "title": "Look for profile name on Facebook", "type": "boolean", "description": "If checked Facebook social profile will be checked.", "default": true }, "scrapeInstagram": { "title": "Look for profile name on Instagram", "type": "boolean", "description": "If checked Instagram social profile will be checked.", "default": true }, "scrapeTiktok": { "title": "Look for profile name on TikTok", "type": "boolean", "description": "If checked TikTok social profile will be checked.", "default": 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 } } } } } } } } }}š¤ Social Media Sentiment Analysis Tool OpenAPI definition
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 Social Media Sentiment Analysis Tool from the options below:
If youād like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients:
