# EU DSA Content Moderation Trends API (`hamzamihaidaniel/eu-dsa-content-moderation-trends-api`) Actor Analyze official EU DSA content-moderation aggregates by platform, violation, automation, action, and date. - **URL**: https://apify.com/hamzamihaidaniel/eu-dsa-content-moderation-trends-api.md - **Developed by:** [Hamza Mihai Daniel](https://apify.com/hamzamihaidaniel) (community) - **Categories:** Automation, Developer tools, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $20.00 / 1,000 trend results 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/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 ## EU DSA Content Moderation Trends API Turn the European Commission's official Digital Services Act Transparency Database aggregates into ranked, analysis-ready moderation trends. The Actor downloads public monthly aggregate archives and groups millions of statements of reasons by platform, violation category, month or day, automation level, decision ground, content source, and moderation action. ### What you can analyze - Which platforms report the most moderation decisions - The leading violation categories for a platform - Fully automated versus partially or non-automated decisions - Content removals, demotions, labels, account actions, and other measures - Daily or monthly changes across up to 12 available months - A platform, category, action, or decision-ground subset Useful applications include trust-and-safety intelligence, policy research, regulatory monitoring, social-media analysis, journalism, and compliance dashboards. ### Input ```json { "monthsBack": 3, "platforms": ["TikTok"], "categories": [], "automation": "all", "decisionGrounds": [], "actions": ["content_removed", "content_demoted", "content_labelled"], "groupBy": ["platform", "category", "month"], "maxResults": 100 } ```` `monthTo` is optional and uses `YYYY-MM`. When omitted, the Actor probes backward from the previous calendar month and skips archives that have not yet been published. Platform and category filters use exact values from the official aggregate dataset. Leave them empty to include all values. ### Output Each dataset item is one ranked aggregate row: ```json { "platform": "TikTok", "category": "STATEMENT_CATEGORY_SCAMS_AND_FRAUD", "date": null, "month": "2026-05", "automation": null, "decisionGround": null, "sourceType": null, "action": null, "statementCount": 426322, "shareOfFilteredStatements": 0.01130007, "monthFrom": "2026-05", "monthTo": "2026-05", "sourceUrl": "https://transparency.dsa.ec.europa.eu/explore-data/download", "retrievedAt": "2026-07-23T17:00:00.000Z" } ``` Results are sorted by `statementCount`. `shareOfFilteredStatements` is the row's fraction of all statements that passed the filters. When grouping by `action`, one underlying statement can contain multiple actions, so action shares may overlap and need not sum to 1. The `REPORT` record in the default key-value store includes available and missing months, source archive URLs, raw and matched aggregate row counts, returned and charged results, filters, and completion status. ### API example ```bash curl "https://api.apify.com/v2/acts/YOUR_USERNAME~eu-dsa-content-moderation-trends-api/run-sync-get-dataset-items?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"monthsBack":1,"monthTo":"2026-05","platforms":["TikTok"],"groupBy":["platform","category","month"],"maxResults":20}' ``` ### Reliability and safety - Uses public monthly aggregates from the official European Commission DSA Transparency Database - Enforces strict compressed and uncompressed archive limits - Rejects unsafe ZIP paths and malformed CSV structures - Handles the source's escaped platform names - Limits each run to 12 months and 500 output rows - Emits only aggregate statistics, not user-level content - Writes data only after filters and ranking have completed The Actor is an independent analytics tool and is not affiliated with or endorsed by the European Commission. It does not provide legal advice. Always follow the official source link when a result is used for compliance or research decisions. ### Official source - DSA Transparency Database data download: https://transparency.dsa.ec.europa.eu/explore-data/download - Official data documentation: https://dsa.pages.code.europa.eu/transparency-database/dsa-tdb/data\_sources.html # Actor input Schema ## `monthsBack` (type: `integer`): Number of available monthly aggregate archives to combine. ## `monthTo` (type: `string`): Optional latest archive month in YYYY-MM format. If empty, the Actor probes backwards from last month. ## `platforms` (type: `array`): Optional exact platform names, for example TikTok, Google Play, or Discord Netherlands B.V. ## `categories` (type: `array`): Optional exact DSA category codes, such as STATEMENT\_CATEGORY\_SCAMS\_AND\_FRAUD. ## `automation` (type: `string`): Filter by how automated the platform's moderation decision was. ## `decisionGrounds` (type: `array`): Optional exact grounds, such as DECISION\_GROUND\_INCOMPATIBLE\_CONTENT. ## `actions` (type: `array`): Actions that a row must contain. When grouped by action, one trend row is created for each matching action. ## `groupBy` (type: `array`): Dimensions used to generate and rank trend rows. ## `maxResults` (type: `integer`): Maximum ranked aggregate rows written to the dataset. ## Actor input object example ```json { "monthsBack": 3, "platforms": [], "categories": [], "automation": "all", "decisionGrounds": [], "actions": [ "content_removed", "content_disabled", "content_demoted", "content_age_restricted", "content_interaction_restricted", "content_labelled", "visibility_other", "account_action", "monetary_action", "service_provision_action" ], "groupBy": [ "platform", "category", "month" ], "maxResults": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `summary` (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("hamzamihaidaniel/eu-dsa-content-moderation-trends-api").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("hamzamihaidaniel/eu-dsa-content-moderation-trends-api").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 hamzamihaidaniel/eu-dsa-content-moderation-trends-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=hamzamihaidaniel/eu-dsa-content-moderation-trends-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "EU DSA Content Moderation Trends API", "description": "Analyze official EU DSA content-moderation aggregates by platform, violation, automation, action, and date.", "version": "0.1", "x-build-id": "NsD5pmsPvetGTH1bB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/hamzamihaidaniel~eu-dsa-content-moderation-trends-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-hamzamihaidaniel-eu-dsa-content-moderation-trends-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/hamzamihaidaniel~eu-dsa-content-moderation-trends-api/runs": { "post": { "operationId": "runs-sync-hamzamihaidaniel-eu-dsa-content-moderation-trends-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/hamzamihaidaniel~eu-dsa-content-moderation-trends-api/run-sync": { "post": { "operationId": "run-sync-hamzamihaidaniel-eu-dsa-content-moderation-trends-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "monthsBack": { "title": "Months to analyze", "minimum": 1, "maximum": 12, "type": "integer", "description": "Number of available monthly aggregate archives to combine.", "default": 3 }, "monthTo": { "title": "Latest month", "pattern": "^\\d{4}-(0[1-9]|1[0-2])$", "type": "string", "description": "Optional latest archive month in YYYY-MM format. If empty, the Actor probes backwards from last month." }, "platforms": { "title": "Platforms", "uniqueItems": true, "type": "array", "description": "Optional exact platform names, for example TikTok, Google Play, or Discord Netherlands B.V.", "items": { "type": "string" }, "default": [] }, "categories": { "title": "Violation categories", "uniqueItems": true, "type": "array", "description": "Optional exact DSA category codes, such as STATEMENT_CATEGORY_SCAMS_AND_FRAUD.", "items": { "type": "string" }, "default": [] }, "automation": { "title": "Decision automation", "enum": [ "all", "AUTOMATED_DECISION_FULLY", "AUTOMATED_DECISION_PARTIALLY", "AUTOMATED_DECISION_NOT_AUTOMATED" ], "type": "string", "description": "Filter by how automated the platform's moderation decision was.", "default": "all" }, "decisionGrounds": { "title": "Decision grounds", "uniqueItems": true, "type": "array", "description": "Optional exact grounds, such as DECISION_GROUND_INCOMPATIBLE_CONTENT.", "items": { "type": "string" }, "default": [] }, "actions": { "title": "Moderation actions", "minItems": 1, "uniqueItems": true, "type": "array", "description": "Actions that a row must contain. When grouped by action, one trend row is created for each matching action.", "items": { "type": "string", "enum": [ "content_removed", "content_disabled", "content_demoted", "content_age_restricted", "content_interaction_restricted", "content_labelled", "visibility_other", "account_action", "monetary_action", "service_provision_action" ], "enumTitles": [ "Content removed", "Content disabled", "Content demoted", "Age restricted", "Interaction restricted", "Content labelled", "Other visibility action", "Account action", "Monetary action", "Service provision action" ] }, "default": [ "content_removed", "content_disabled", "content_demoted", "content_age_restricted", "content_interaction_restricted", "content_labelled", "visibility_other", "account_action", "monetary_action", "service_provision_action" ] }, "groupBy": { "title": "Group results by", "minItems": 1, "uniqueItems": true, "type": "array", "description": "Dimensions used to generate and rank trend rows.", "items": { "type": "string", "enum": [ "platform", "category", "date", "month", "automation", "decisionGround", "sourceType", "action" ], "enumTitles": [ "Platform", "Violation category", "Day", "Month", "Decision automation", "Decision ground", "Source type", "Moderation action" ] }, "default": [ "platform", "category", "month" ] }, "maxResults": { "title": "Maximum trend rows", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum ranked aggregate rows written to the dataset.", "default": 100 } } }, "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 } } } } } } } } } } ```