# WeChat Official Account Comment Sentiment & Consumer Insights (`scrupulous_buckler/wechat-official-account-comment-sentiment-consumer-insights`) Actor Turn WeChat Official Account article comments into sentiment, recurring questions, needs, objections, purchase signals, supplied brand and competitor mentions, evidence quotes, and content opportunities. - **URL**: https://apify.com/scrupulous\_buckler/wechat-official-account-comment-sentiment-consumer-insights.md - **Developed by:** [Peng Lyu](https://apify.com/scrupulous_buckler) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / official account comment insights report This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## WeChat Official Account Comment Sentiment & Consumer Insights Turn WeChat Official Account article comments and reply threads into evidence-linked consumer questions, needs, objections, purchase signals, supplied brand and competitor mentions, usage scenarios, and content opportunities. **Unofficial tool. This Actor is not affiliated with, sponsored by, or endorsed by Tencent, WeChat, Weixin, or any upstream data provider.** ### This is the analysis layer Raw WeChat article scrapers return comment rows. This Actor returns: - one normalized classification per comment or reply - transparent positive, negative, mixed, question, or neutral labels - recurring reader questions, needs, concerns, and intent signals - exact buyer-supplied brand, product, and competitor mentions - comparison and purchase-intent evidence - article-by-article discussion differences - ranked content opportunities backed by comment excerpts - optional regulated-topic claim-risk screening - explicit sample and coverage warnings The classification is deterministic and auditable. The Actor does not claim to use AI and does not automatically invent or discover brand names. ### Four input modes 1. **Static preview** — eight synthetic comments across three articles, without triggering the $4.99 custom report event. 2. **Live article comments** — one to ten public `mp.weixin.qq.com` URLs. 3. **Apify Datasets** — comments already collected by another Actor. 4. **Uploaded comments** — strings or JSON objects supplied by the customer. Live mode calls the separate `sian.agency/wechat-official-account-data-scraper` for comments and optional reply threads. Its charges are billed separately by Apify. ### Pricing One successful live, Dataset, or uploaded-data report costs **$4.99** and analyzes up to **100 comments and replies**. The built-in static preview does not trigger the custom report event; Apify may still show the small Actor-start or platform usage charge. If no usable comments are collected or matched, no paid report is created. ### Example ```json { "mode": "liveArticleComments", "articleUrls": [ {"url": "https://mp.weixin.qq.com/s/EXAMPLE"} ], "topic": "Low-sugar breakfast reader questions", "commentKeywords": ["价格", "成分", "副作用", "哪里买"], "knownEntities": ["品牌甲"], "competitorNames": ["品牌乙"], "maxTotalComments": 100 } ```` ### Important limits - Many articles expose no public comments. - Results describe the collected sample, not every reader. - Sentiment and themes use transparent cue dictionaries and may miss context. - Exact names must be supplied to measure brands and competitors reliably. - Comments are discussion evidence, not medical, scientific, or legal proof. ### Local validation ```bash python3 -m unittest discover -s tests -v ``` # Actor input Schema ## `mode` (type: `string`): Run the example, collect public comments from article URLs, analyze Apify Datasets, or paste comments. ## `articleUrls` (type: `array`): One to ten public mp.weixin.qq.com article links. Used only in live mode. ## `datasetId` (type: `string`): Dataset from a WeChat Official Account scraper or another compatible export. ## `sourceDatasetIds` (type: `array`): Optional additional Apify Datasets containing article comments or replies. ## `uploadedComments` (type: `array`): Paste strings or JSON records. Common comment, author, likes, article, publisher and reply fields are recognized. ## `topic` (type: `string`): Product, campaign, category or reader question used to label the report. ## `commentKeywords` (type: `array`): Examples: price, side effects, where to buy, product names, campaign phrases or use cases. ## `requireKeywordMatch` (type: `boolean`): Off by default so surrounding conversation context is preserved. ## `knownEntities` (type: `array`): Exact names to measure. The Actor does not automatically discover every possible brand. ## `competitorNames` (type: `array`): Exact competitor brand or product names to identify and compare. ## `includeReplies` (type: `boolean`): Requests replies for a limited number of comments when upstream IDs are available. Extra upstream calls may incur separate charges. ## `maxReplyThreads` (type: `integer`): Limits the number of extra upstream reply-thread calls made in live mode. ## `maxTotalComments` (type: `integer`): One $4.99 report analyzes at most 100 normalized comments and replies. ## `maxCommentsPerArticle` (type: `integer`): Limits top-level comment collection for each supplied article before optional replies. ## `maxEvidence` (type: `integer`): Limits auditable source-comment excerpts returned in each report section. ## `maxOpportunities` (type: `integer`): Limits the number of evidence-linked content opportunities returned. ## `regulatedTopic` (type: `boolean`): Adds risky-claim evidence and safer framing. This is a screening aid, not legal or medical approval. ## `includeSourceComments` (type: `boolean`): Keeps the normalized source rows embedded in the report for audit and export. ## `upstreamMaxChargeUsd` (type: `number`): Maximum allowed charge for each upstream comment/reply run. This is separate from the $4.99 analysis report. ## Actor input object example ```json { "mode": "demo", "articleUrls": [], "datasetId": "", "sourceDatasetIds": [], "uploadedComments": [], "topic": "WeChat Official Account reader discussion", "commentKeywords": [], "requireKeywordMatch": false, "knownEntities": [], "competitorNames": [], "includeReplies": true, "maxReplyThreads": 5, "maxTotalComments": 100, "maxCommentsPerArticle": 50, "maxEvidence": 20, "maxOpportunities": 10, "regulatedTopic": false, "includeSourceComments": true, "upstreamMaxChargeUsd": 5 } ``` # Actor output Schema ## `report` (type: `string`): No description ## `comments` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("scrupulous_buckler/wechat-official-account-comment-sentiment-consumer-insights").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("scrupulous_buckler/wechat-official-account-comment-sentiment-consumer-insights").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call scrupulous_buckler/wechat-official-account-comment-sentiment-consumer-insights --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrupulous_buckler/wechat-official-account-comment-sentiment-consumer-insights", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "WeChat Official Account Comment Sentiment & Consumer Insights", "description": "Turn WeChat Official Account article comments into sentiment, recurring questions, needs, objections, purchase signals, supplied brand and competitor mentions, evidence quotes, and content opportunities.", "version": "0.1", "x-build-id": "mnxJKRp0EvSaVkjne" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrupulous_buckler~wechat-official-account-comment-sentiment-consumer-insights/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrupulous_buckler-wechat-official-account-comment-sentiment-consumer-insights", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrupulous_buckler~wechat-official-account-comment-sentiment-consumer-insights/runs": { "post": { "operationId": "runs-sync-scrupulous_buckler-wechat-official-account-comment-sentiment-consumer-insights", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrupulous_buckler~wechat-official-account-comment-sentiment-consumer-insights/run-sync": { "post": { "operationId": "run-sync-scrupulous_buckler-wechat-official-account-comment-sentiment-consumer-insights", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "mode": { "title": "Data source", "enum": [ "demo", "liveArticleComments", "datasetComments", "uploadedComments" ], "type": "string", "description": "Run the example, collect public comments from article URLs, analyze Apify Datasets, or paste comments.", "default": "demo" }, "articleUrls": { "title": "WeChat Official Account article URLs", "type": "array", "description": "One to ten public mp.weixin.qq.com article links. Used only in live mode.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "datasetId": { "title": "Primary comments Dataset ID", "type": "string", "description": "Dataset from a WeChat Official Account scraper or another compatible export.", "default": "" }, "sourceDatasetIds": { "title": "Additional comment Dataset IDs", "type": "array", "description": "Optional additional Apify Datasets containing article comments or replies.", "default": [], "items": { "type": "string" } }, "uploadedComments": { "title": "Uploaded comments", "type": "array", "description": "Paste strings or JSON records. Common comment, author, likes, article, publisher and reply fields are recognized.", "default": [] }, "topic": { "title": "Research topic", "type": "string", "description": "Product, campaign, category or reader question used to label the report.", "default": "WeChat Official Account reader discussion" }, "commentKeywords": { "title": "Keywords to measure inside comments", "type": "array", "description": "Examples: price, side effects, where to buy, product names, campaign phrases or use cases.", "default": [], "items": { "type": "string" } }, "requireKeywordMatch": { "title": "Analyze only comments matching a keyword", "type": "boolean", "description": "Off by default so surrounding conversation context is preserved.", "default": false }, "knownEntities": { "title": "Brands, products and other exact names", "type": "array", "description": "Exact names to measure. The Actor does not automatically discover every possible brand.", "default": [], "items": { "type": "string" } }, "competitorNames": { "title": "Competitor names", "type": "array", "description": "Exact competitor brand or product names to identify and compare.", "default": [], "items": { "type": "string" } }, "includeReplies": { "title": "Collect reply threads in live mode", "type": "boolean", "description": "Requests replies for a limited number of comments when upstream IDs are available. Extra upstream calls may incur separate charges.", "default": true }, "maxReplyThreads": { "title": "Maximum reply threads", "minimum": 0, "maximum": 10, "type": "integer", "description": "Limits the number of extra upstream reply-thread calls made in live mode.", "default": 5 }, "maxTotalComments": { "title": "Comments and replies to analyze (maximum 100)", "minimum": 1, "maximum": 100, "type": "integer", "description": "One $4.99 report analyzes at most 100 normalized comments and replies.", "default": 100 }, "maxCommentsPerArticle": { "title": "Maximum top-level comments per article", "minimum": 1, "maximum": 100, "type": "integer", "description": "Limits top-level comment collection for each supplied article before optional replies.", "default": 50 }, "maxEvidence": { "title": "Maximum evidence excerpts per report section", "minimum": 5, "maximum": 100, "type": "integer", "description": "Limits auditable source-comment excerpts returned in each report section.", "default": 20 }, "maxOpportunities": { "title": "Maximum content opportunities", "minimum": 1, "maximum": 30, "type": "integer", "description": "Limits the number of evidence-linked content opportunities returned.", "default": 10 }, "regulatedTopic": { "title": "Health or other regulated topic", "type": "boolean", "description": "Adds risky-claim evidence and safer framing. This is a screening aid, not legal or medical approval.", "default": false }, "includeSourceComments": { "title": "Keep normalized source comments inside the report", "type": "boolean", "description": "Keeps the normalized source rows embedded in the report for audit and export.", "default": true }, "upstreamMaxChargeUsd": { "title": "Maximum separate upstream charge per call", "minimum": 0.1, "maximum": 20, "type": "number", "description": "Maximum allowed charge for each upstream comment/reply run. This is separate from the $4.99 analysis report.", "default": 5 } } }, "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 } } } } } } } } } } ```