Twitter Trends Scraper

Twitter Trends Scraper

Twitter Trends Scraper extracts trending topics from X (Twitter) without the official API. It collects trending hashtags/keywords, estimated tweet volumes, and timestamps from public trend pages to give marketers, developers, data analysts, and researchers a fast, reliable view of what’s taking off right now. As a real-time Twitter trends scraper and Twitter trending topics scraper by location, it helps you monitor conversations globally or locally and scale historical tracking with repeatable runs.

What data / output can you get?

Below are the exact fields the actor saves to the Apify dataset (one record per trend):

Data type	Description	Example value
time	UTC timestamp when the trend was parsed and saved	2026-04-16T12:34:56.789Z
timePeriod	Time window the URL represents (e.g., Live, 1 hour ago, Yesterday)	Live
trend	Trend text (hashtag or keyword)	#LaCasaDeLosFamososMx3
volume	Volume text as shown on the page (may be empty if unavailable)	35.2K tweets

Bonus: The actor also saves a run summary to the Key-Value store as RUN_SUMMARY.json, including:

• runStartedAt (UTC time)
• proxyUsed (e.g., NO_PROXY, APIFY_PROXY, APIFY_RESIDENTIAL_FALLBACK)
• stats.total_items, stats.per_timePeriod, and stats.failed_urls

You can download dataset results in common formats (JSON, CSV, Excel) from the Apify platform for analysis and reporting.

Key features

• 🌍 Country-specific or worldwide trends Get worldwide results or choose a country to run a precise Twitter trends scraper by location using the country input.

• ⏱️ Live and historical snapshots Scrape Live trends or historical windows: 1–23 hours ago, Yesterday, a Week Ago, a Month Ago, a Year Ago, and a legacy Day 3 option. Ideal for a real-time Twitter trends scraper and for tracking trend evolution.

• 🔁 Robust retries with live row-by-row saving Built-in HTTP retries with exponential backoff and live dataset pushing ensure you don’t lose partial data when a request fails.

• 🛡️ Smart proxy handling with automatic fallback Use Apify Proxy or your own settings. If the selected proxy is rejected, the actor automatically falls back to Apify RESIDENTIAL.

• ⚡ Lightweight, fast scraping Efficient HTTP fetching and HTML parsing (no headless browser) make this a reliable Twitter trends scraping tool for scale.

• 📦 Easy exports Results are stored in the Apify dataset so you can export to JSON, CSV, or Excel and feed BI dashboards or pipelines.

• 🧑‍💻 Developer-friendly Built as an Apify Actor with clean JSON outputs, suitable for Python workflows and API-driven pipelines. Perfect if you need a Twitter trends crawler or an X trends scraper you can automate.

How to use Twitter Trends Scraper - step by step

1. Sign in to Apify Log in to your Apify account to access and run the actor.

2. Open the Twitter-Trends-Scraper Find “Twitter Trends Scraper” in your console or Apify Store and click Try it.

3. Choose your time windows Toggle Live for current trends, or select any historical flags (e.g., 1 hour ago through 23 hours ago, Yesterday, Week Ago, Month Ago, Year Ago, Day 3).

4. (Optional) Select a country Use the Country dropdown to run a Twitter local trends scraper for a specific market. Leave empty for worldwide.

5. Configure Proxy configuration (optional) Use the built-in Apify proxy editor if needed. If a selected proxy is rejected, the actor automatically falls back to Apify RESIDENTIAL.

6. Run the actor Click Start. The actor fetches pages, retries on failures, and pushes each parsed trend row-by-row to the dataset.

7. Download your results Open the run’s Dataset tab to preview and export data to JSON, CSV, or Excel. A RUN_SUMMARY.json file is also saved in the Key-Value store for quick run diagnostics.

Pro Tip: Need custom snapshots? Advanced users can supply their own URLs and schedule runs on Apify to build a historical time series across multiple locations and time windows—great for “Twitter trending topics without API” monitoring.

Use cases

Use case name	Description
Marketing & content planning	Identify trending hashtags and keywords to shape copy, campaigns, and posting schedules using a Twitter trending topics scraper.
Social listening without API	Scrape Twitter trending hashtags from public pages to monitor conversations when API access is limited or unavailable.
Regional trend tracking	Run a Twitter local trends scraper to track country-level momentum and compare markets side by side.
Newsroom & editorial planning	Spot emerging topics early and prioritize coverage with a real-time Twitter trends scraper.
Academic & media research	Build structured historical datasets for studies of discourse, events, and cultural shifts with a Twitter trends data scraper.
Data engineering pipelines	Automate periodic runs and export to CSV/JSON for ETL into warehouses and analytics systems with a Twitter trends crawler.

Why choose Twitter Trends Scraper?

This actor is built for precision, automation, and reliability—without relying on fragile browser automation.

• ✅ Accurate, structured outputs: Clean JSON with time, timePeriod, trend, and volume fields.
• 🌐 Worldwide or by location: Flexible country selection makes it a Twitter trends scraper by location.
• ⚖️ Live + historical: Capture Live and hourly/day snapshots for trend evolution.
• 🔁 Built-in resilience: Automatic retries and live dataset pushing reduce data loss.
• 🛡️ Production-ready proxying: Smart Apify Proxy fallback to RESIDENTIAL enhances stability at scale.
• 🧑‍💻 Developer access: Works seamlessly with API-driven and Python-based data workflows.
• 💾 Easy exports: Download from the Apify dataset in JSON, CSV, or Excel—no extra tooling needed.

In short: a dependable X trending topics scraper designed for repeatable, scalable data collection—far more robust than browser extensions or ad-hoc scripts.

Is it legal / ethical to use Twitter Trends Scraper?

Yes—when used responsibly. This actor collects publicly available trend information from getdaytrends.com that reflects X (Twitter) trending topics. It does not access private profiles or authenticated data.

Guidelines for compliant use:

• Only collect public data you’re allowed to access.
• Respect the terms of service of target sites and platforms.
• Follow relevant regulations (e.g., GDPR, CCPA) and your organization’s data policies.
• Do not attempt to scrape private information, DMs, or protected accounts.
• Consult your legal team for edge cases or jurisdiction-specific questions.

Input parameters & output format

Example JSON input

{
  "live": true,
  "hour1": true,
  "yesterday": true,
  "weekAgo": false,
  "monthAgo": false,
  "yearAgo": false,
  "day2": false,
  "day3": false,
  "country": "US",
  "proxy": {
    "useApifyProxy": true
  }
}

Parameters

Field	Type	Description	Default	Required
live	boolean	Scrape the current live trends.	Not specified	No
hour1	boolean	Scrape trends from 1 hour ago.	Not specified	No
hour2	boolean	Scrape trends from 2 hours ago.	Not specified	No
hour3	boolean	Scrape trends from 3 hours ago.	Not specified	No
hour4	boolean	Scrape trends from 4 hours ago.	Not specified	No
hour5	boolean	Scrape trends from 5 hours ago.	Not specified	No
hour6	boolean	Scrape trends from 6 hours ago.	Not specified	No
hour7	boolean	Scrape trends from 7 hours ago.	Not specified	No
hour8	boolean	Scrape trends from 8 hours ago.	Not specified	No
hour9	boolean	Scrape trends from 9 hours ago.	Not specified	No
hour10	boolean	Scrape trends from 10 hours ago.	Not specified	No
hour11	boolean	Scrape trends from 11 hours ago.	Not specified	No
hour12	boolean	Scrape trends from 12 hours ago.	Not specified	No
hour13	boolean	Scrape trends from 13 hours ago.	Not specified	No
hour14	boolean	Scrape trends from 14 hours ago.	Not specified	No
hour15	boolean	Scrape trends from 15 hours ago.	Not specified	No
hour16	boolean	Scrape trends from 16 hours ago.	Not specified	No
hour17	boolean	Scrape trends from 17 hours ago.	Not specified	No
hour18	boolean	Scrape trends from 18 hours ago.	Not specified	No
hour19	boolean	Scrape trends from 19 hours ago.	Not specified	No
hour20	boolean	Scrape trends from 20 hours ago.	Not specified	No
hour21	boolean	Scrape trends from 21 hours ago.	Not specified	No
hour22	boolean	Scrape trends from 22 hours ago.	Not specified	No
hour23	boolean	Scrape trends from 23 hours ago.	Not specified	No
yesterday	boolean	Scrape yesterday's full-day summary.	Not specified	No
weekAgo	boolean	Scrape trends from 1 week ago.	Not specified	No
monthAgo	boolean	Scrape trends from 1 month ago.	Not specified	No
yearAgo	boolean	Scrape trends from 1 year ago.	Not specified	No
day2	boolean	Day 2 (Yesterday) - legacy option, same as 'yesterday'.	Not specified	No
day3	boolean	Scrape the summary from 2 days ago.	Not specified	No
country	string (enum)	Select a country to scrape country-specific Twitter trends. Leave empty for worldwide trends.	"" (Worldwide)	No
proxy	object	Proxy configuration. Defaults to no proxy. If the selected proxy is rejected, the actor falls back to Apify RESIDENTIAL automatically.	No proxy	No

Example JSON output (dataset)

[
  {
    "time": "2026-04-16T12:34:56.789Z",
    "timePeriod": "Live",
    "trend": "#LaCasaDeLosFamososMx3",
    "volume": "35.2K tweets"
  },
  {
    "time": "2026-04-16T12:34:56.789Z",
    "timePeriod": "1 hour ago",
    "trend": "Giants",
    "volume": "100.8K tweets"
  }
]

Example RUN_SUMMARY.json (Key-Value store)

{
  "runStartedAt": "2026-04-16T12:34:56.789Z",
  "proxyUsed": "APIFY_RESIDENTIAL_FALLBACK",
  "stats": {
    "total_items": 50,
    "per_timePeriod": {
      "Live": 25,
      "1 hour ago": 25
    },
    "failed_urls": []
  }
}

Note: volume may be an empty string if the page doesn’t display a count for a given trend.

FAQ

Does this Twitter Trends Scraper use the Twitter API?

No. It scrapes publicly available trend pages from getdaytrends.com, making it a Twitter trends scraper without API access. This is ideal when you need an X trends scraper that works reliably without keys or rate limits.

Can I scrape by location?

Yes. Set the Country input to run a Twitter trends scraper by location. Leave it empty to collect worldwide trends.

What fields are returned in the dataset?

Each record includes time, timePeriod, trend, and volume. This keeps outputs clean and consistent for downstream analytics and reporting.

How real-time is the data?

You can capture Live trends and historical snapshots (1–23 hours ago, Yesterday, Week Ago, Month Ago, Year Ago). This supports both a real-time Twitter trends scraper and longer-term historical analysis.

How many results will I get per run?

The actor parses all available trend rows on each requested page. The exact count varies by timePeriod and location. The RUN_SUMMARY.json includes total_items and per_timePeriod counts for each run.

What happens if my proxy gets blocked?

The actor tests the selected proxy and automatically falls back to Apify RESIDENTIAL when the proxy is rejected. This improves stability for large-scale runs of your Twitter trending topics scraper.

How do I export the results?

Open the run’s Dataset and export to JSON, CSV, or Excel. This makes it easy to feed dashboards, notebooks, or BI tools in your Twitter trends scraping tool workflow.

Is it legal to scrape these trends?

Yes—when done responsibly with public data. Avoid private or authenticated content and ensure you respect the terms of service for target sites and applicable data regulations.

Final thoughts

Twitter Trends Scraper is built for reliable, structured extraction of trending topics and volumes from X (Twitter) via public trend pages. It combines real-time and historical coverage, location targeting, robust retries, and proxy fallback to support marketers, developers, analysts, and researchers at scale. Use the Apify dataset exports for seamless handoff to analytics pipelines, or integrate with your own Python/API workflows. Start capturing smarter “Twitter trending topics without API” data and turn conversation momentum into actionable insight.