# China Social Sentiment Aggregate (`nexgendata/china-social-sentiment-aggregate`) Actor One keyword → a normalized, deduped, sentiment-tagged feed across Chinese social platforms (Bilibili + RedNote + Weibo). Cross-platform China brand & topic monitoring for AI-training data, brand sentiment and China-equity analysts. - **URL**: https://apify.com/nexgendata/china-social-sentiment-aggregate.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Social media, AI, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $250.00 / 1,000 sentiment report (per keyword)s 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## 🇨🇳 China Social Sentiment — Cross-Platform Brand & Topic Monitor Give it **one keyword** (Chinese or English) and get back a **single, unified, deduplicated, sentiment-tagged feed** of Chinese social posts — pulled from multiple platforms in one run, normalized to one schema. Built for **brand monitoring, China consumer & equity research, and AI training data**. ### What you get A flat list of posts, one row per item, each normalized to the same shape: | Field | Meaning | |---|---| | `platform` | `bilibili` / `rednote` / `weibo` | | `title`, `text` | post title and body/《caption》 | | `author`, `url`, `source_url` | creator and links | | `likes`, `comments`, `shares`, `views` | engagement (where the platform exposes it) | | `posted_at` | publish time | | `sentiment_label`, `sentiment_score` | best-effort bilingual sentiment (see below) | | `keyword`, `scraped_at` | your query + capture time | Duplicate posts (same URL/id) are removed across platforms. ### Platform coverage — read this before you run Coverage differs by platform, so results vary with your keyword: - **Bilibili (B站) — primary, works out of the box.** Full anonymous keyword video search. This is the reliable engine and the default. - **Weibo Hot Search (微博热搜) — situational.** Contributes items only when your keyword matches a **currently-trending** Hot-Search topic (with English translation). For non-trending keywords it returns nothing — that's expected. - **RedNote / Xiaohongshu (小红书) — requires a login cookie.** XHS forces a login modal on anonymous keyword search, so RedNote keyword search returns nothing without an authenticated session. It is **not** enabled by default here. ### Sentiment Each item is tagged `positive` / `negative` / `neutral` with a score, using a **lightweight bilingual (Chinese + English) lexicon**. It's best-effort signal for triage and monitoring — **not** a substitute for a trained sentiment model. ### Pricing & billing - **Flat $0.25 per keyword run** — charged **once** per run, and **only when results are returned** (an empty run costs nothing). - This actor orchestrates NexGenData's platform scrapers under **your** Apify account, so the underlying Bilibili/RedNote/Weibo scrapers bill **your** account per their own pay-per-event pricing. The $0.25 is only the aggregation + sentiment layer on top. ### Input | Field | Default | Notes | |---|---|---| | `keyword` | *(required)* | brand / product / person / topic, Chinese or English | | `platforms` | `["bilibili","weibo"]` | choose any of bilibili / rednote / weibo | | `max_per_platform` | `50` | items pulled per platform before dedup | | `sentiment` | `true` | toggle sentiment tagging | # Actor input Schema ## `keyword` (type: `string`): The brand, product, person or topic to monitor across Chinese social platforms (Chinese or English). ## `platforms` (type: `array`): Which Chinese social platforms to aggregate. Bilibili = full anonymous keyword video search (primary). Weibo = contributes only when your keyword matches a currently-trending Hot-Search topic. RedNote/Xiaohongshu keyword search requires a logged-in cookie (XHS blocks anonymous search) and will return nothing without one. ## `max_per_platform` (type: `integer`): How many items to pull from each platform before normalizing and deduping. ## `sentiment` (type: `boolean`): Tag each item with a best-effort bilingual sentiment label (positive / negative / neutral) and score. Lexicon-based, not a substitute for a trained model. ## Actor input object example ```json { "keyword": "泡泡玛特", "platforms": [ "bilibili", "weibo" ], "max_per_platform": 50, "sentiment": true } ```` # 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 = { "keyword": "泡泡玛特", "platforms": [ "bilibili", "weibo" ], "max_per_platform": 50, "sentiment": true }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/china-social-sentiment-aggregate").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 = { "keyword": "泡泡玛特", "platforms": [ "bilibili", "weibo", ], "max_per_platform": 50, "sentiment": True, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/china-social-sentiment-aggregate").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 '{ "keyword": "泡泡玛特", "platforms": [ "bilibili", "weibo" ], "max_per_platform": 50, "sentiment": true }' | apify call nexgendata/china-social-sentiment-aggregate --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/china-social-sentiment-aggregate", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "China Social Sentiment Aggregate", "description": "One keyword → a normalized, deduped, sentiment-tagged feed across Chinese social platforms (Bilibili + RedNote + Weibo). Cross-platform China brand & topic monitoring for AI-training data, brand sentiment and China-equity analysts.", "version": "0.0", "x-build-id": "UII16mxhPIknMVSl4" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~china-social-sentiment-aggregate/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-china-social-sentiment-aggregate", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~china-social-sentiment-aggregate/runs": { "post": { "operationId": "runs-sync-nexgendata-china-social-sentiment-aggregate", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~china-social-sentiment-aggregate/run-sync": { "post": { "operationId": "run-sync-nexgendata-china-social-sentiment-aggregate", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "keyword" ], "properties": { "keyword": { "title": "Keyword / brand / topic", "type": "string", "description": "The brand, product, person or topic to monitor across Chinese social platforms (Chinese or English)." }, "platforms": { "title": "Platforms", "type": "array", "description": "Which Chinese social platforms to aggregate. Bilibili = full anonymous keyword video search (primary). Weibo = contributes only when your keyword matches a currently-trending Hot-Search topic. RedNote/Xiaohongshu keyword search requires a logged-in cookie (XHS blocks anonymous search) and will return nothing without one.", "items": { "type": "string", "enum": [ "bilibili", "rednote", "weibo" ], "enumTitles": [ "Bilibili (B站) — anonymous keyword search", "RedNote / Xiaohongshu (小红书) — needs login cookie", "Weibo Hot Search (微博热搜) — trending-topic match" ] }, "default": [ "bilibili", "weibo" ] }, "max_per_platform": { "title": "Max items per platform", "minimum": 1, "maximum": 200, "type": "integer", "description": "How many items to pull from each platform before normalizing and deduping.", "default": 50 }, "sentiment": { "title": "Add best-effort sentiment tags", "type": "boolean", "description": "Tag each item with a best-effort bilingual sentiment label (positive / negative / neutral) and score. Lexicon-based, not a substitute for a trained model.", "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 } } } } } } } } } } ```