# X.com (Twitter) Trends & Trending Topics Scraper (`lurkapi/x-twitter-trends-scraper`) Actor Scrape trending topics from X.com by country or city. Live trends plus optional historical snapshots (1h to 7d) and top posts per trend. Pay per row, undercuts every competitor on base price. - **URL**: https://apify.com/lurkapi/x-twitter-trends-scraper.md - **Developed by:** [LurkAPI](https://apify.com/lurkapi) (community) - **Categories:** Agents, Automation, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $0.05 / 1,000 live trend rows 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 ## X.com (Twitter) Trends & Trending Topics Scraper See what's trending on X before your competitors do. Live top-50 trends for 467 countries and cities, plus the rank history that tells you if a hashtag is climbing or dying. Rewind to any date going back two years and get the trend list that was live at that moment. ### 🎁 What you get #### 🔥 Live trends wherever your audience is Top 50 trending topics for any of 467 locations. Every country plus 404 real per-city feeds including Tokyo, New York, London, São Paulo, Mumbai, and Berlin. #### 📈 See a trend before it peaks Every location returns the rank a hashtag held 1, 3, 6, 12, and 24 hours ago, plus 2, 3, and 7 days back. A hashtag at rank 3 this morning and rank 20 now is on the way out. A brand new one in the 1h list that was not in the 3h list is breaking. This is how content teams time posts. #### 🎯 See who's already winning under a trend Pull the highest-engagement posts sitting under any trend. Author, text, likes, retweets, replies, views. Filter for verified accounts only, media-only, minimum likes, or language, so you get a clean list of who to study or beat. ### 👥 Built for - **Social media managers** picking today's hashtag before standup - **Content teams** researching what's already viral - **Agencies** running weekly trend reports for clients - **Newsrooms** watching for stories breaking in specific countries - **Trading desks** hunting alpha in crypto and meme sentiment ### 📋 How to use it 1. Add one or more locations from the dropdown. Type to search. Examples: `worldwide`, `japan`, `united-states`, `japan/tokyo`. 2. Pick how many trends per location. The prefill of 20 lands in about 15 seconds on the default plan. 3. Turn on any add-ons you want: historical snapshots (1h to 7 days), past-date lookup, or top posts per trend. All off by default. 4. Hit Start. The `status` field on every output row tells you whether the row is a real result or an explanation of what went wrong. ### 🌍 Geographic coverage - **62 countries**, from the United States, Japan, and the United Kingdom to smaller markets like Belarus, Guatemala, and Kuwait. - **404 cities**, from Tokyo, Osaka, and New York to smaller metros like Blackpool, Winnipeg, and Recife. Every city returns its own trend list, not the parent country's. - **Worldwide**: the global top-50 trend list. Total: 467 supported locations. Pick from the Locations dropdown as a country name (`japan`), a country/city (`japan/tokyo`), or `worldwide`. The dropdown filters as you type. ### 💰 Pricing Pay-per-event. | What you pay for | Price | |---------------------------------|-------------| | Live trend row | $0.05 / 1,000 | | Historical snapshot trend row | $0.05 / 1,000 | | Top post row (add-on) | $3.00 / 1,000 | You are only charged when a row lands in your dataset. Failed lookups, unresolved locations, and filtered-out trends are always free. ### 💡 Good to know - **Historical snapshots and past-date lookups work for country and worldwide inputs.** City inputs return the current snapshot only. - **Rank drift beats volume for timing signal.** If a hashtag was at rank 3 six hours ago and rank 20 now, it's fading. If a new one shows up in the 1h list that was not in the 3h list, it's breaking. - **Real tweet volumes on pre-January 2026 dates.** X removed live volume counts on January 13, 2026. Our archive kept them on every hour before then. ### ❓ FAQ **Which locations are supported?** 467 total: 62 countries and 404 cities. Includes the US, Japan, UK, Brazil, India, Mexico, plus metros like Tokyo, New York, London, São Paulo, Mumbai, Berlin, and hundreds more. Start typing in the Locations dropdown to filter the list. **Can I compare the same hashtag across countries?** Yes. List every country you care about in one run. Each trend row is tagged with its location so filtering downstream is a one-liner. **Does it work for non-English trends?** Yes. Japanese, Korean, Arabic, Hindi, Russian, and every other script return as-is. **What if I want to check what was trending on a specific past day?** Set the historicalDate field to any date going back two years. You get the trend list that was live at noon UTC on that day, or any other hour you pick. **How current is the live data?** Live trends match what X's own trend widget is showing right now. Historical windows (1h, 3h, 6h, 12h, 24h, 2d, 3d, 7d) come with the exact timestamp they were snapshotted. **Why is the tweet volume empty on live trends?** X pulled tweet volume counts from the public trend feed in January 2026. Every trend scraper on the platform returns null for volume on live trends now. Rank, name, and search URL still come through on every row. **Do I get charged for failed lookups?** No. Only rows that land in your dataset are billed. Unresolved locations, filtered-out trends, and failed source fetches are always free. **Can I run this on a schedule?** Yes. Schedule daily or hourly in Apify Console and pipe the dataset into Sheets, BigQuery, Slack, or your own API. ### 🔗 Other tools you might like - [X Tweet Scraper](https://apify.com/lurkapi/x-twitter-tweet-scraper). Scrape tweets by search query, handle, or URL. - [X Follower Scraper](https://apify.com/lurkapi/x-twitter-follower-scraper). Pull the follower and following lists of any public account. - [X Video, Photo & GIF Downloader](https://apify.com/lurkapi/x-twitter-video-photo-gif-downloader). Download photos, videos, and GIFs from posts. - [X Community Post Scraper](https://apify.com/lurkapi/x-twitter-community-post-scraper). Extract posts from any X community. ### ⚖️ Disclaimer By using this Actor you agree to comply with X's Terms of Service and all applicable laws. Do not use scraped data to harass individuals or infringe on privacy. Data is provided as-is with no warranty of accuracy or completeness. Volumes and rankings reflect what the source displayed at scrape time and can change minute to minute. **Keywords**: X trends scraper, Twitter trends scraper, trending topics, trending hashtags, X trending topics, Twitter trending topics, X hashtag tracker, trend monitoring, real-time trends, Japan trends, US trends, historical trends, top posts per trend. # Actor input Schema ## `locations` (type: `array`): Type or pick from the dropdown to add a country (japan), city (japan/tokyo), or worldwide. Search for a metro to filter the list. Full list of 467 supported locations shown in the dropdown. ## `keywordInclude` (type: `string`): Keep only trends whose name matches this regex. Case-insensitive. Example: ai|crypto ## `keywordExclude` (type: `string`): Drop trends whose name matches this regex. Case-insensitive. Example: nsfw|spam ## `categoryInclude` (type: `array`): Hidden. X made the ExplorePage endpoint login-only in Jan 2026; category enrichment is unreachable in guest mode. Field kept for backwards compatibility with saved tasks. ## `sortBy` (type: `string`): Trend ordering. Rank uses X's own order (recommended). ## `maxTrendsPerLocation` (type: `integer`): Cap on how many trends come back per location. If you enable historical snapshots, this cap applies per window. ## `historicalWindows` (type: `array`): Fetch archived trend snapshots for each window. Empty = live only. 1h/3h/6h/12h/24h come from a fresh hourly archive. 2d/3d/7d come from a daily archive that goes back years. Country and worldwide only. ## `historicalDate` (type: `string`): Pick a past date and hour to fetch the trend list that was live at that moment. Goes back two years. ## `historicalHour` (type: `integer`): Hour of the day (0-23, UTC) for the Historical date. Default 12. ## `includeTopPosts` (type: `boolean`): For each trend, fetch the top N posts on X. Charged per post row returned. ## `topPostsPerTrend` (type: `integer`): How many top posts to fetch per trend. Only used when the Top posts add-on is on. Maximum 20 per trend. ## `topPostsMinLikes` (type: `integer`): Drop posts below this like count. Only used when the Top posts add-on is on. 0 means no minimum. ## `topPostsVerifiedOnly` (type: `boolean`): Drop posts from unverified accounts. Only applied to the top posts add-on. ## `topPostsHasMediaOnly` (type: `boolean`): Keep only posts with attached photo or video. Only applied to the top posts add-on. ## `topPostsLangCode` (type: `string`): Keep only posts in this language. Default: any language. ## `outputRowType` (type: `boolean`): Row discriminator: trend or post. ## `outputLocation` (type: `boolean`): Requested location string (country or country/city). ## `outputWoeid` (type: `boolean`): Resolved Yahoo WOEID for this location. ## `outputWindow` (type: `boolean`): Snapshot window (live, 1h, 3h, ...) for trend rows. ## `outputRank` (type: `boolean`): Rank in the trend list (1-based). ## `outputName` (type: `boolean`): Trend text (hashtag or phrase). ## `outputTweetVolume` (type: `boolean`): Tweet volume when known (null when unknown). ## `outputCategory` (type: `boolean`): Hidden (category source is not reachable). ## `outputContext` (type: `boolean`): Hidden (context source is not reachable). ## `outputUrl` (type: `boolean`): Search URL on X for this trend. ## `outputScrapedAt` (type: `boolean`): ISO-8601 timestamp of when the trend was scraped. ## `outputPostFields` (type: `boolean`): Post-specific columns (id, url, fullText, author, likeCount, retweetCount, replyCount, viewCount) on post rows. ## Actor input object example ```json { "locations": [ "worldwide", "japan", "united-states/new-york" ], "categoryInclude": [], "sortBy": "rank", "maxTrendsPerLocation": 20, "historicalWindows": [], "historicalDate": "", "historicalHour": 12, "includeTopPosts": false, "topPostsPerTrend": 10, "topPostsMinLikes": 0, "topPostsVerifiedOnly": false, "topPostsHasMediaOnly": false, "topPostsLangCode": "", "outputRowType": true, "outputLocation": true, "outputWoeid": true, "outputWindow": true, "outputRank": true, "outputName": true, "outputTweetVolume": true, "outputCategory": false, "outputContext": false, "outputUrl": true, "outputScrapedAt": true, "outputPostFields": true } ```` # Actor output Schema ## `overview` (type: `string`): Status, type, location, window, rank, trend, volume, category, URL. ## `trends` (type: `string`): Every trend row, live plus historical when the add-on is enabled. ## `posts` (type: `string`): Top posts per trend when the Top posts add-on is enabled. ## `locations` (type: `string`): Trend rows grouped by location and window. # 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 = { "locations": [ "worldwide", "japan", "united-states/new-york" ], "categoryInclude": [], "maxTrendsPerLocation": 20, "historicalWindows": [] }; // Run the Actor and wait for it to finish const run = await client.actor("lurkapi/x-twitter-trends-scraper").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 = { "locations": [ "worldwide", "japan", "united-states/new-york", ], "categoryInclude": [], "maxTrendsPerLocation": 20, "historicalWindows": [], } # Run the Actor and wait for it to finish run = client.actor("lurkapi/x-twitter-trends-scraper").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 '{ "locations": [ "worldwide", "japan", "united-states/new-york" ], "categoryInclude": [], "maxTrendsPerLocation": 20, "historicalWindows": [] }' | apify call lurkapi/x-twitter-trends-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lurkapi/x-twitter-trends-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "X.com (Twitter) Trends & Trending Topics Scraper", "description": "Scrape trending topics from X.com by country or city. Live trends plus optional historical snapshots (1h to 7d) and top posts per trend. Pay per row, undercuts every competitor on base price.", "version": "0.0", "x-build-id": "IVwNO9K5SyhALR96v" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lurkapi~x-twitter-trends-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lurkapi-x-twitter-trends-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lurkapi~x-twitter-trends-scraper/runs": { "post": { "operationId": "runs-sync-lurkapi-x-twitter-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lurkapi~x-twitter-trends-scraper/run-sync": { "post": { "operationId": "run-sync-lurkapi-x-twitter-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "locations": { "title": "Locations", "type": "array", "description": "Type or pick from the dropdown to add a country (japan), city (japan/tokyo), or worldwide. Search for a metro to filter the list. Full list of 467 supported locations shown in the dropdown.", "items": { "type": "string", "enum": [ "worldwide", "algeria", "algeria/algiers", "argentina", "argentina/buenos-aires", "argentina/cordoba", "argentina/mendoza", "argentina/rosario", "australia", "australia/adelaide", "australia/brisbane", "australia/canberra", "australia/darwin", "australia/melbourne", "australia/perth", "australia/sydney", "austria", "austria/vienna", "bahrain", "belarus", "belarus/brest", "belarus/gomel", "belarus/grodno", "belarus/minsk", "belgium", "brazil", "brazil/belo-horizonte", "brazil/belem", "brazil/brasilia", "brazil/campinas", "brazil/curitiba", "brazil/fortaleza", "brazil/goiania", "brazil/guarulhos", "brazil/manaus", "brazil/porto-alegre", "brazil/recife", "brazil/rio-de-janeiro", "brazil/salvador", "brazil/sao-luis", "brazil/sao-paulo", "canada", "canada/calgary", "canada/edmonton", "canada/montreal", "canada/ottawa", "canada/quebec", "canada/toronto", "canada/vancouver", "canada/winnipeg", "chile", "chile/concepcion", "chile/santiago", "chile/valparaiso", "colombia", "colombia/barranquilla", "colombia/bogota", "colombia/cali", "colombia/medellin", "denmark", "dominican-republic", "dominican-republic/santo-domingo", "ecuador", "ecuador/guayaquil", "ecuador/quito", "egypt", "egypt/alexandria", "egypt/cairo", "egypt/giza", "france", "france/bordeaux", "france/lille", "france/lyon", "france/marseille", "france/montpellier", "france/nantes", "france/paris", "france/rennes", "france/strasbourg", "france/toulouse", "germany", "germany/berlin", "germany/bremen", "germany/cologne", "germany/dortmund", "germany/dresden", "germany/dusseldorf", "germany/essen", "germany/frankfurt", "germany/hamburg", "germany/leipzig", "germany/munich", "germany/stuttgart", "ghana", "ghana/accra", "ghana/kumasi", "greece", "greece/athens", "greece/thessaloniki", "guatemala", "guatemala/guatemala-city", "india", "india/ahmedabad", "india/amritsar", "india/bangalore", "india/bhopal", "india/chennai", "india/delhi", "india/hyderabad", "india/indore", "india/jaipur", "india/kanpur", "india/kolkata", "india/lucknow", "india/mumbai", "india/nagpur", "india/patna", "india/pune", "india/rajkot", "india/ranchi", "india/srinagar", "india/surat", "india/thane", "indonesia", "indonesia/bandung", "indonesia/bekasi", "indonesia/depok", "indonesia/jakarta", "indonesia/makassar", "indonesia/medan", "indonesia/palembang", "indonesia/pekanbaru", "indonesia/semarang", "indonesia/surabaya", "indonesia/tangerang", "ireland", "ireland/cork", "ireland/dublin", "ireland/galway", "israel", "israel/haifa", "israel/jerusalem", "israel/tel-aviv", "italy", "italy/bologna", "italy/genoa", "italy/milan", "italy/naples", "italy/palermo", "italy/rome", "italy/turin", "japan", "japan/chiba", "japan/fukuoka", "japan/hamamatsu", "japan/hiroshima", "japan/kawasaki", "japan/kitakyushu", "japan/kobe", "japan/kumamoto", "japan/kyoto", "japan/nagoya", "japan/niigata", "japan/okayama", "japan/okinawa", "japan/osaka", "japan/sagamihara", "japan/saitama", "japan/sapporo", "japan/sendai", "japan/takamatsu", "japan/tokyo", "japan/yokohama", "jordan", "jordan/amman", "kenya", "kenya/mombasa", "kenya/nairobi", "korea", "korea/ansan", "korea/bucheon", "korea/busan", "korea/changwon", "korea/daegu", "korea/daejeon", "korea/goyang", "korea/gwangju", "korea/incheon", "korea/seongnam", "korea/seoul", "korea/suwon", "korea/ulsan", "korea/yongin", "kuwait", "latvia", "latvia/riga", "lebanon", "malaysia", "malaysia/hulu-langat", "malaysia/ipoh", "malaysia/johor-bahru", "malaysia/kajang", "malaysia/klang", "malaysia/kuala-lumpur", "malaysia/petaling", "mexico", "mexico/acapulco", "mexico/aguascalientes", "mexico/chihuahua", "mexico/ciudad-juarez", "mexico/culiacan", "mexico/ecatepec-de-morelos", "mexico/guadalajara", "mexico/hermosillo", "mexico/leon", "mexico/mexicali", "mexico/mexico-city", "mexico/monterrey", "mexico/morelia", "mexico/merida", "mexico/naucalpan-de-juarez", "mexico/nezahualcoyotl", "mexico/puebla", "mexico/queretaro", "mexico/saltillo", "mexico/san-luis-potosi", "mexico/tijuana", "mexico/toluca", "mexico/zapopan", "netherlands", "netherlands/amsterdam", "netherlands/den-haag", "netherlands/rotterdam", "netherlands/utrecht", "new-zealand", "new-zealand/auckland", "nigeria", "nigeria/benin-city", "nigeria/ibadan", "nigeria/kaduna", "nigeria/kano", "nigeria/lagos", "nigeria/port-harcourt", "norway", "norway/bergen", "norway/oslo", "oman", "oman/muscat", "pakistan", "pakistan/faisalabad", "pakistan/karachi", "pakistan/lahore", "pakistan/multan", "pakistan/rawalpindi", "panama", "peru", "peru/lima", "philippines", "philippines/antipolo", "philippines/cagayan-de-oro", "philippines/calocan", "philippines/cebu-city", "philippines/davao-city", "philippines/makati", "philippines/manila", "philippines/pasig", "philippines/quezon-city", "philippines/taguig", "philippines/zamboanga-city", "poland", "poland/gdansk", "poland/krakow", "poland/lodz", "poland/poznan", "poland/warsaw", "poland/wroclaw", "portugal", "puerto-rico", "qatar", "russia", "russia/chelyabinsk", "russia/irkutsk", "russia/kazan", "russia/khabarovsk", "russia/krasnodar", "russia/krasnoyarsk", "russia/moscow", "russia/nizhny-novgorod", "russia/novosibirsk", "russia/omsk", "russia/perm", "russia/rostov-on-don", "russia/saint-petersburg", "russia/samara", "russia/ufa", "russia/vladivostok", "russia/volgograd", "russia/voronezh", "russia/yekaterinburg", "saudi-arabia", "saudi-arabia/ahsa", "saudi-arabia/dammam", "saudi-arabia/jeddah", "saudi-arabia/mecca", "saudi-arabia/medina", "saudi-arabia/riyadh", "singapore", "singapore/singapore", "south-africa", "south-africa/cape-town", "south-africa/durban", "south-africa/johannesburg", "south-africa/port-elizabeth", "south-africa/pretoria", "south-africa/soweto", "spain", "spain/barcelona", "spain/bilbao", "spain/las-palmas", "spain/madrid", "spain/malaga", "spain/murcia", "spain/palma", "spain/seville", "spain/valencia", "spain/zaragoza", "sweden", "sweden/gothenburg", "sweden/stockholm", "switzerland", "switzerland/geneva", "switzerland/lausanne", "switzerland/zurich", "thailand", "thailand/bangkok", "turkey", "turkey/adana", "turkey/ankara", "turkey/antalya", "turkey/bursa", "turkey/diyarbakr", "turkey/eskisehir", "turkey/gaziantep", "turkey/istanbul", "turkey/izmir", "turkey/kayseri", "turkey/konya", "turkey/mersin", "ukraine", "ukraine/dnipropetrovsk", "ukraine/donetsk", "ukraine/kharkiv", "ukraine/kyiv", "ukraine/lviv", "ukraine/odesa", "ukraine/zaporozhye", "united-arab-emirates", "united-arab-emirates/abu-dhabi", "united-arab-emirates/dubai", "united-arab-emirates/sharjah", "united-kingdom", "united-kingdom/belfast", "united-kingdom/birmingham", "united-kingdom/blackpool", "united-kingdom/bournemouth", "united-kingdom/brighton", "united-kingdom/bristol", "united-kingdom/cardiff", "united-kingdom/coventry", "united-kingdom/derby", "united-kingdom/edinburgh", "united-kingdom/glasgow", "united-kingdom/hull", "united-kingdom/leeds", "united-kingdom/leicester", "united-kingdom/liverpool", "united-kingdom/london", "united-kingdom/manchester", "united-kingdom/middlesbrough", "united-kingdom/newcastle", "united-kingdom/nottingham", "united-kingdom/plymouth", "united-kingdom/portsmouth", "united-kingdom/preston", "united-kingdom/sheffield", "united-kingdom/stoke-on-trent", "united-kingdom/swansea", "united-states", "united-states/albuquerque", "united-states/atlanta", "united-states/austin", "united-states/baltimore", "united-states/baton-rouge", "united-states/birmingham", "united-states/boston", "united-states/charlotte", "united-states/chicago", "united-states/cincinnati", "united-states/cleveland", "united-states/colorado-springs", "united-states/columbus", "united-states/dallas-ft-worth", "united-states/denver", "united-states/detroit", "united-states/el-paso", "united-states/fresno", "united-states/greensboro", "united-states/harrisburg", "united-states/honolulu", "united-states/houston", "united-states/indianapolis", "united-states/jackson", "united-states/jacksonville", "united-states/kansas-city", "united-states/las-vegas", "united-states/long-beach", "united-states/los-angeles", "united-states/louisville", "united-states/memphis", "united-states/mesa", "united-states/miami", "united-states/milwaukee", "united-states/minneapolis", "united-states/nashville", "united-states/new-haven", "united-states/new-orleans", "united-states/new-york", "united-states/norfolk", "united-states/oklahoma-city", "united-states/omaha", "united-states/orlando", "united-states/philadelphia", "united-states/phoenix", "united-states/pittsburgh", "united-states/portland", "united-states/providence", "united-states/raleigh", "united-states/richmond", "united-states/sacramento", "united-states/salt-lake-city", "united-states/san-antonio", "united-states/san-diego", "united-states/san-francisco", "united-states/san-jose", "united-states/seattle", "united-states/st-louis", "united-states/tallahassee", "united-states/tampa", "united-states/tucson", "united-states/virginia-beach", "united-states/washington", "venezuela", "venezuela/barcelona", "venezuela/barquisimeto", "venezuela/caracas", "venezuela/ciudad-guayana", "venezuela/maracaibo", "venezuela/maracay", "venezuela/maturin", "venezuela/turmero", "venezuela/valencia", "vietnam", "vietnam/can-tho", "vietnam/da-nang", "vietnam/hai-phong", "vietnam/hanoi", "vietnam/ho-chi-minh-city" ], "enumTitles": [ "🌍 Worldwide", "Algeria", "Algeria / Algiers", "Argentina", "Argentina / Buenos Aires", "Argentina / Córdoba", "Argentina / Mendoza", "Argentina / Rosario", "Australia", "Australia / Adelaide", "Australia / Brisbane", "Australia / Canberra", "Australia / Darwin", "Australia / Melbourne", "Australia / Perth", "Australia / Sydney", "Austria", "Austria / Vienna", "Bahrain", "Belarus", "Belarus / Brest", "Belarus / Gomel", "Belarus / Grodno", "Belarus / Minsk", "Belgium", "Brazil", "Brazil / Belo Horizonte", "Brazil / Belém", "Brazil / Brasília", "Brazil / Campinas", "Brazil / Curitiba", "Brazil / Fortaleza", "Brazil / Goiânia", "Brazil / Guarulhos", "Brazil / Manaus", "Brazil / Porto Alegre", "Brazil / Recife", "Brazil / Rio de Janeiro", "Brazil / Salvador", "Brazil / São Luís", "Brazil / São Paulo", "Canada", "Canada / Calgary", "Canada / Edmonton", "Canada / Montreal", "Canada / Ottawa", "Canada / Quebec", "Canada / Toronto", "Canada / Vancouver", "Canada / Winnipeg", "Chile", "Chile / Concepcion", "Chile / Santiago", "Chile / Valparaiso", "Colombia", "Colombia / Barranquilla", "Colombia / Bogotá", "Colombia / Cali", "Colombia / Medellín", "Denmark", "Dominican Republic", "Dominican Republic / Santo Domingo", "Ecuador", "Ecuador / Guayaquil", "Ecuador / Quito", "Egypt", "Egypt / Alexandria", "Egypt / Cairo", "Egypt / Giza", "France", "France / Bordeaux", "France / Lille", "France / Lyon", "France / Marseille", "France / Montpellier", "France / Nantes", "France / Paris", "France / Rennes", "France / Strasbourg", "France / Toulouse", "Germany", "Germany / Berlin", "Germany / Bremen", "Germany / Cologne", "Germany / Dortmund", "Germany / Dresden", "Germany / Dusseldorf", "Germany / Essen", "Germany / Frankfurt", "Germany / Hamburg", "Germany / Leipzig", "Germany / Munich", "Germany / Stuttgart", "Ghana", "Ghana / Accra", "Ghana / Kumasi", "Greece", "Greece / Athens", "Greece / Thessaloniki", "Guatemala", "Guatemala / Guatemala City", "India", "India / Ahmedabad", "India / Amritsar", "India / Bangalore", "India / Bhopal", "India / Chennai", "India / Delhi", "India / Hyderabad", "India / Indore", "India / Jaipur", "India / Kanpur", "India / Kolkata", "India / Lucknow", "India / Mumbai", "India / Nagpur", "India / Patna", "India / Pune", "India / Rajkot", "India / Ranchi", "India / Srinagar", "India / Surat", "India / Thane", "Indonesia", "Indonesia / Bandung", "Indonesia / Bekasi", "Indonesia / Depok", "Indonesia / Jakarta", "Indonesia / Makassar", "Indonesia / Medan", "Indonesia / Palembang", "Indonesia / Pekanbaru", "Indonesia / Semarang", "Indonesia / Surabaya", "Indonesia / Tangerang", "Ireland", "Ireland / Cork", "Ireland / Dublin", "Ireland / Galway", "Israel", "Israel / Haifa", "Israel / Jerusalem", "Israel / Tel Aviv", "Italy", "Italy / Bologna", "Italy / Genoa", "Italy / Milan", "Italy / Naples", "Italy / Palermo", "Italy / Rome", "Italy / Turin", "Japan", "Japan / Chiba", "Japan / Fukuoka", "Japan / Hamamatsu", "Japan / Hiroshima", "Japan / Kawasaki", "Japan / Kitakyushu", "Japan / Kobe", "Japan / Kumamoto", "Japan / Kyoto", "Japan / Nagoya", "Japan / Niigata", "Japan / Okayama", "Japan / Okinawa", "Japan / Osaka", "Japan / Sagamihara", "Japan / Saitama", "Japan / Sapporo", "Japan / Sendai", "Japan / Takamatsu", "Japan / Tokyo", "Japan / Yokohama", "Jordan", "Jordan / Amman", "Kenya", "Kenya / Mombasa", "Kenya / Nairobi", "Korea", "Korea / Ansan", "Korea / Bucheon", "Korea / Busan", "Korea / Changwon", "Korea / Daegu", "Korea / Daejeon", "Korea / Goyang", "Korea / Gwangju", "Korea / Incheon", "Korea / Seongnam", "Korea / Seoul", "Korea / Suwon", "Korea / Ulsan", "Korea / Yongin", "Kuwait", "Latvia", "Latvia / Riga", "Lebanon", "Malaysia", "Malaysia / Hulu Langat", "Malaysia / Ipoh", "Malaysia / Johor Bahru", "Malaysia / Kajang", "Malaysia / Klang", "Malaysia / Kuala Lumpur", "Malaysia / Petaling", "Mexico", "Mexico / Acapulco", "Mexico / Aguascalientes", "Mexico / Chihuahua", "Mexico / Ciudad Juarez", "Mexico / Culiacán", "Mexico / Ecatepec de Morelos", "Mexico / Guadalajara", "Mexico / Hermosillo", "Mexico / León", "Mexico / Mexicali", "Mexico / Mexico City", "Mexico / Monterrey", "Mexico / Morelia", "Mexico / Mérida", "Mexico / Naucalpan de Juárez", "Mexico / Nezahualcóyotl", "Mexico / Puebla", "Mexico / Querétaro", "Mexico / Saltillo", "Mexico / San Luis Potosí", "Mexico / Tijuana", "Mexico / Toluca", "Mexico / Zapopan", "Netherlands", "Netherlands / Amsterdam", "Netherlands / Den Haag", "Netherlands / Rotterdam", "Netherlands / Utrecht", "New Zealand", "New Zealand / Auckland", "Nigeria", "Nigeria / Benin City", "Nigeria / Ibadan", "Nigeria / Kaduna", "Nigeria / Kano", "Nigeria / Lagos", "Nigeria / Port Harcourt", "Norway", "Norway / Bergen", "Norway / Oslo", "Oman", "Oman / Muscat", "Pakistan", "Pakistan / Faisalabad", "Pakistan / Karachi", "Pakistan / Lahore", "Pakistan / Multan", "Pakistan / Rawalpindi", "Panama", "Peru", "Peru / Lima", "Philippines", "Philippines / Antipolo", "Philippines / Cagayan de Oro", "Philippines / Calocan", "Philippines / Cebu City", "Philippines / Davao City", "Philippines / Makati", "Philippines / Manila", "Philippines / Pasig", "Philippines / Quezon City", "Philippines / Taguig", "Philippines / Zamboanga City", "Poland", "Poland / Gdańsk", "Poland / Kraków", "Poland / Lodz", "Poland / Poznań", "Poland / Warsaw", "Poland / Wroclaw", "Portugal", "Puerto Rico", "Qatar", "Russia", "Russia / Chelyabinsk", "Russia / Irkutsk", "Russia / Kazan", "Russia / Khabarovsk", "Russia / Krasnodar", "Russia / Krasnoyarsk", "Russia / Moscow", "Russia / Nizhny Novgorod", "Russia / Novosibirsk", "Russia / Omsk", "Russia / Perm", "Russia / Rostov-on-Don", "Russia / Saint Petersburg", "Russia / Samara", "Russia / Ufa", "Russia / Vladivostok", "Russia / Volgograd", "Russia / Voronezh", "Russia / Yekaterinburg", "Saudi Arabia", "Saudi Arabia / Ahsa", "Saudi Arabia / Dammam", "Saudi Arabia / Jeddah", "Saudi Arabia / Mecca", "Saudi Arabia / Medina", "Saudi Arabia / Riyadh", "Singapore", "Singapore / Singapore", "South Africa", "South Africa / Cape Town", "South Africa / Durban", "South Africa / Johannesburg", "South Africa / Port Elizabeth", "South Africa / Pretoria", "South Africa / Soweto", "Spain", "Spain / Barcelona", "Spain / Bilbao", "Spain / Las Palmas", "Spain / Madrid", "Spain / Malaga", "Spain / Murcia", "Spain / Palma", "Spain / Seville", "Spain / Valencia", "Spain / Zaragoza", "Sweden", "Sweden / Gothenburg", "Sweden / Stockholm", "Switzerland", "Switzerland / Geneva", "Switzerland / Lausanne", "Switzerland / Zurich", "Thailand", "Thailand / Bangkok", "Turkey", "Turkey / Adana", "Turkey / Ankara", "Turkey / Antalya", "Turkey / Bursa", "Turkey / Diyarbakır", "Turkey / Eskişehir", "Turkey / Gaziantep", "Turkey / Istanbul", "Turkey / Izmir", "Turkey / Kayseri", "Turkey / Konya", "Turkey / Mersin", "Ukraine", "Ukraine / Dnipropetrovsk", "Ukraine / Donetsk", "Ukraine / Kharkiv", "Ukraine / Kyiv", "Ukraine / Lviv", "Ukraine / Odesa", "Ukraine / Zaporozhye", "United Arab Emirates", "United Arab Emirates / Abu Dhabi", "United Arab Emirates / Dubai", "United Arab Emirates / Sharjah", "United Kingdom", "United Kingdom / Belfast", "United Kingdom / Birmingham", "United Kingdom / Blackpool", "United Kingdom / Bournemouth", "United Kingdom / Brighton", "United Kingdom / Bristol", "United Kingdom / Cardiff", "United Kingdom / Coventry", "United Kingdom / Derby", "United Kingdom / Edinburgh", "United Kingdom / Glasgow", "United Kingdom / Hull", "United Kingdom / Leeds", "United Kingdom / Leicester", "United Kingdom / Liverpool", "United Kingdom / London", "United Kingdom / Manchester", "United Kingdom / Middlesbrough", "United Kingdom / Newcastle", "United Kingdom / Nottingham", "United Kingdom / Plymouth", "United Kingdom / Portsmouth", "United Kingdom / Preston", "United Kingdom / Sheffield", "United Kingdom / Stoke-on-Trent", "United Kingdom / Swansea", "United States", "United States / Albuquerque", "United States / Atlanta", "United States / Austin", "United States / Baltimore", "United States / Baton Rouge", "United States / Birmingham", "United States / Boston", "United States / Charlotte", "United States / Chicago", "United States / Cincinnati", "United States / Cleveland", "United States / Colorado Springs", "United States / Columbus", "United States / Dallas-Ft. Worth", "United States / Denver", "United States / Detroit", "United States / El Paso", "United States / Fresno", "United States / Greensboro", "United States / Harrisburg", "United States / Honolulu", "United States / Houston", "United States / Indianapolis", "United States / Jackson", "United States / Jacksonville", "United States / Kansas City", "United States / Las Vegas", "United States / Long Beach", "United States / Los Angeles", "United States / Louisville", "United States / Memphis", "United States / Mesa", "United States / Miami", "United States / Milwaukee", "United States / Minneapolis", "United States / Nashville", "United States / New Haven", "United States / New Orleans", "United States / New York", "United States / Norfolk", "United States / Oklahoma City", "United States / Omaha", "United States / Orlando", "United States / Philadelphia", "United States / Phoenix", "United States / Pittsburgh", "United States / Portland", "United States / Providence", "United States / Raleigh", "United States / Richmond", "United States / Sacramento", "United States / Salt Lake City", "United States / San Antonio", "United States / San Diego", "United States / San Francisco", "United States / San Jose", "United States / Seattle", "United States / St. Louis", "United States / Tallahassee", "United States / Tampa", "United States / Tucson", "United States / Virginia Beach", "United States / Washington", "Venezuela", "Venezuela / Barcelona", "Venezuela / Barquisimeto", "Venezuela / Caracas", "Venezuela / Ciudad Guayana", "Venezuela / Maracaibo", "Venezuela / Maracay", "Venezuela / Maturín", "Venezuela / Turmero", "Venezuela / Valencia", "Vietnam", "Vietnam / Can Tho", "Vietnam / Da Nang", "Vietnam / Hai Phong", "Vietnam / Hanoi", "Vietnam / Ho Chi Minh City" ] } }, "keywordInclude": { "title": "Keyword include (regex)", "type": "string", "description": "Keep only trends whose name matches this regex. Case-insensitive. Example: ai|crypto" }, "keywordExclude": { "title": "Keyword exclude (regex)", "type": "string", "description": "Drop trends whose name matches this regex. Case-insensitive. Example: nsfw|spam" }, "categoryInclude": { "title": "Category include", "type": "array", "description": "Hidden. X made the ExplorePage endpoint login-only in Jan 2026; category enrichment is unreachable in guest mode. Field kept for backwards compatibility with saved tasks.", "items": { "type": "string" } }, "sortBy": { "title": "Sort trends by", "enum": [ "rank", "name-asc", "name-desc" ], "type": "string", "description": "Trend ordering. Rank uses X's own order (recommended).", "default": "rank" }, "maxTrendsPerLocation": { "title": "Max trends per location", "minimum": 1, "maximum": 50, "type": "integer", "description": "Cap on how many trends come back per location. If you enable historical snapshots, this cap applies per window.", "default": 30 }, "historicalWindows": { "title": "Historical snapshots ($)", "type": "array", "description": "Fetch archived trend snapshots for each window. Empty = live only. 1h/3h/6h/12h/24h come from a fresh hourly archive. 2d/3d/7d come from a daily archive that goes back years. Country and worldwide only.", "items": { "type": "string", "enum": [ "1h", "3h", "6h", "12h", "24h", "2d", "3d", "7d" ], "enumTitles": [ "1h ago", "3h ago", "6h ago", "12h ago", "24h ago", "2d ago", "3d ago", "7d ago" ] } }, "historicalDate": { "title": "Historical date ($)", "type": "string", "description": "Pick a past date and hour to fetch the trend list that was live at that moment. Goes back two years.", "default": "" }, "historicalHour": { "title": "Historical date: hour (UTC)", "minimum": 0, "maximum": 23, "type": "integer", "description": "Hour of the day (0-23, UTC) for the Historical date. Default 12.", "default": 12 }, "includeTopPosts": { "title": "Top posts per trend ($)", "type": "boolean", "description": "For each trend, fetch the top N posts on X. Charged per post row returned.", "default": false }, "topPostsPerTrend": { "title": "Top posts per trend (count)", "minimum": 1, "maximum": 20, "type": "integer", "description": "How many top posts to fetch per trend. Only used when the Top posts add-on is on. Maximum 20 per trend.", "default": 10 }, "topPostsMinLikes": { "title": "Top posts: minimum likes", "minimum": 0, "type": "integer", "description": "Drop posts below this like count. Only used when the Top posts add-on is on. 0 means no minimum.", "default": 0 }, "topPostsVerifiedOnly": { "title": "Top posts: verified authors only", "type": "boolean", "description": "Drop posts from unverified accounts. Only applied to the top posts add-on.", "default": false }, "topPostsHasMediaOnly": { "title": "Top posts: must have media", "type": "boolean", "description": "Keep only posts with attached photo or video. Only applied to the top posts add-on.", "default": false }, "topPostsLangCode": { "title": "Top posts: language", "enum": [ "", "en", "ja", "es", "pt", "ar", "ko", "fr", "de", "id", "tr", "ru", "it", "th", "hi", "nl", "pl", "sv", "zh", "vi", "fa", "ro", "uk", "he", "el", "cs", "hu", "no", "da", "fi", "bg", "ms", "ca" ], "type": "string", "description": "Keep only posts in this language. Default: any language.", "default": "" }, "outputRowType": { "title": "rowType", "type": "boolean", "description": "Row discriminator: trend or post.", "default": true }, "outputLocation": { "title": "location", "type": "boolean", "description": "Requested location string (country or country/city).", "default": true }, "outputWoeid": { "title": "woeid", "type": "boolean", "description": "Resolved Yahoo WOEID for this location.", "default": true }, "outputWindow": { "title": "window", "type": "boolean", "description": "Snapshot window (live, 1h, 3h, ...) for trend rows.", "default": true }, "outputRank": { "title": "rank", "type": "boolean", "description": "Rank in the trend list (1-based).", "default": true }, "outputName": { "title": "name", "type": "boolean", "description": "Trend text (hashtag or phrase).", "default": true }, "outputTweetVolume": { "title": "tweetVolume", "type": "boolean", "description": "Tweet volume when known (null when unknown).", "default": true }, "outputCategory": { "title": "category", "type": "boolean", "description": "Hidden (category source is not reachable).", "default": false }, "outputContext": { "title": "context", "type": "boolean", "description": "Hidden (context source is not reachable).", "default": false }, "outputUrl": { "title": "url", "type": "boolean", "description": "Search URL on X for this trend.", "default": true }, "outputScrapedAt": { "title": "scrapedAt", "type": "boolean", "description": "ISO-8601 timestamp of when the trend was scraped.", "default": true }, "outputPostFields": { "title": "post columns", "type": "boolean", "description": "Post-specific columns (id, url, fullText, author, likeCount, retweetCount, replyCount, viewCount) on post rows.", "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 } } } } } } } } } } ```