Twitter Profile Scraper: Get Profile Tweets + Their Replies 🐦

Extract tweets, profile data, and engagement metrics from any Twitter account. $0.016 per profile includes 40 tweets FREE – pay only for what you scrape. Get tweet text, likes, retweets, replies, views, author details, and media URLs instantly. No authentication required, no proxy setup needed.

💰 Pricing: $0.016 per profile (includes 40 tweets FREE) + $0.0004 per additional tweet/reply
📊 Data Extracted: Tweet text, engagement metrics (likes/retweets/replies/views), author info, timestamps, media
🎁 Generous Free Quota: 40 tweets per profile + 40 replies per reply query included in base price
⚡ Simple Setup: No authentication | No proxy setup | Direct Twitter access | Event-based billing

Perfect for social media monitoring, brand sentiment analysis, competitive intelligence, and market research. Scrape Twitter profiles by username or URL, filter tweets by date range, extract reply threads, and export to JSON/CSV/Excel. Built for marketers, data analysts, researchers, and developers who need reliable Twitter data extraction at transparent pricing.

Key capabilities: bulk profile scraping, tweet replies extraction, date range filtering (2025-10-10 or 2025-11-06_07:00:59_UTC formats), custom data transformation, event-based pricing ($0.0004 per additional tweet/reply). Runs on Apify platform or locally. Scale from 40 tweets to 10,000+ tweets across multiple profiles with predictable costs.

• ℹ️ Disclaimer About This Twitter Profile Scraper
• 🧭 What Does Twitter Profile Scraper Do?
• 🐉 Features and Functionality of Apidojo's Twitter Profile Scraper
• 💰 Pricing: Transparent Event-Based Twitter Scraper Costs
• 💡 Twitter Scraper Input Strategy Guide
• 📦 Output
• 🧩 Custom Map Function
• Twitter Scraper Export
• What Is a Twitter Profile Scraper?
• Features of Our Twitter Profile Scraper
• Input Parameters for Twitter Profile Scraping
• Who Can Benefit From Twitter Profile Scraping?
• Custom Map Function for Advanced Data Processing
• Start Extracting Twitter Data Today
• ❓ Frequently Asked Questions about Twitter Profile Scraping (FAQ)

ℹ️ Disclaimer About This Twitter Profile Scraper

We are data extraction specialists with deep expertise in Twitter profile scraping. This Twitter account scraper is exceptionally fine-tuned for extracting Twitter data by username, URL, and profile ID—offering you comprehensive capabilities for Twitter data extraction. We provide enterprise-grade maintenance, responsive support, and reliable Twitter scraper performance. No marketing fluff—just accurate Twitter profile data and professional service.

What makes us different:

• ✅ Battle-tested across thousands of Twitter extraction projects
• ✅ Direct support from the development team
• ✅ Continuous updates for Twitter platform changes
• ✅ Transparent event-based pricing - only pay for what you scrape
• ✅ No proxy required - direct access to Twitter data

🧭 What Does Twitter Profile Scraper Do?

This Twitter account scraper extracts comprehensive tweet data, reply threads, and engagement metrics from Twitter/X profiles without requiring authentication or proxies. Use this Twitter profile scraper to collect tweet content, author details, and interaction data by username or URL at transparent, event-based pricing.

Core Extraction Capabilities

📊 Tweet Data Extraction

Extract complete tweet information including tweet text, creation timestamps, engagement metrics (likes, retweets, replies, views, quotes, bookmarks), tweet IDs, URLs, conversation IDs, source applications, and language detection. This Twitter extractor retrieves all public tweet data from any Twitter profile using handles or profile URLs.

💬 Reply Thread Scraping

Collect complete reply threads from any tweet with configurable minimum reply thresholds. The Twitter profile scraper extracts each reply's content, author information, engagement metrics, timestamps, and conversation context—perfect for sentiment analysis, viral content research, and community engagement monitoring.

👤 Author Profile Data

Automatically extracts comprehensive author information including username, display name, user ID, verification status (legacy and blue verified), profile pictures, bio descriptions, follower counts, and following counts. This Twitter account scraper captures complete user context for each tweet and reply.

🔍 Multiple Input Methods

• Search by handles: Extract tweets from specific Twitter profiles using @usernames ($0.016 per profile with 40 FREE tweets)
• Search by URLs: Scrape Twitter account details by URL using direct profile links (x.com or twitter.com format)
• Date range filtering: Extract tweets from specific time periods using start and end dates (supports 2025-10-10 or 2025-11-06_07:00:59_UTC formats)
• Bulk profile scraping: Process multiple Twitter accounts simultaneously with predictable per-profile pricing

🎯 Advanced Filtering Options

Control exactly what data you extract with flexible input parameters: set maximum item limits across entire runs, filter tweets by date ranges for campaign analysis, enable reply extraction only for high-engagement tweets (configurable minReplyCount), and transform output data with custom map functions for workflow integration.

🐉 Features and Functionality of Apidojo's Twitter Profile Scraper

Apidojo's Twitter profile scraper combines transparent event-based pricing with powerful tweet extraction capabilities. Get complete Twitter profile data, tweets, replies, and engagement metrics by username or URL with predictable per-profile billing and enterprise-grade features.

Core Features

Feature	Description	Benefit
💰 Event-Based Pricing	Pay only for profiles you actually scrape—no subscriptions, no monthly fees	Cost control: Only pay for what you extract
🎁 40 Free Tweets Per Profile	Every profile query includes first 40 tweets at no extra charge ($0.016 base price)	Budget-friendly: $0.016 gets you 40 complete tweets
🎁 40 Free Replies Per Query	Every reply extraction includes first 40 replies included ($0.016 per reply query)	Conversation analysis: Deep-dive into discussions affordably
🔍 Multiple Input Methods	Extract via @handles, direct Twitter URLs (x.com or twitter.com formats)	Flexibility: Choose username or URL-based extraction
📅 Date Range Filtering	Filter tweets by specific time periods with flexible date formats	Campaign analysis: Extract tweets from product launches, events, or specific periods
💬 Reply Thread Extraction	Complete reply scraping with configurable minimum reply thresholds	Sentiment analysis: Capture conversations and audience reactions
📊 30+ Tweet Data Points	Text, engagement metrics (likes/retweets/replies/views/quotes/bookmarks), author info, timestamps, media URLs	Comprehensive data: Everything needed for social media analysis
👤 Full Author Profiles	Username, display name, user ID, verification status, follower/following counts, bio, profile picture	Influencer research: Complete user context for each tweet
🛡️ Zero Authentication	No Twitter cookies, no login credentials, no account required	Safe & simple: Start scraping immediately without setup
🔧 Custom Map Function	JavaScript function to transform, filter, or enrich output data on-the-fly	Data control: Calculate engagement rates, normalize text, add custom fields
✨ Structured Output	Clean JSON/CSV/Excel export ready for databases, spreadsheets, or APIs	Integration-ready: Import directly into analytics tools
🚀 No Proxy Needed	Direct Twitter data access without residential or datacenter proxies	Cost savings: No proxy fees, simplified infrastructure
⚡ Bulk Profile Processing	Scrape multiple Twitter accounts simultaneously with predictable per-profile costs	Scale efficiently: Process competitor lists, influencer cohorts, brand mentions
🎯 Precise Cost Control	Set maxItems limits, disable replies, adjust date ranges to control spending	Budget management: Never exceed your data extraction budget

Technical Capabilities

• Two flexible date formats: Standard (2025-10-10) and UTC precision (2025-11-06_07:00:59_UTC)
• Reply filtering: Only extract replies from tweets meeting minimum engagement thresholds
• Output transformation: Custom map function supports field addition, modification, and removal
• Multiple export formats: JSON, CSV, Excel, XML, RSS - download via UI or API
• Real-time data access: Get current tweets and engagement metrics on demand
• Scalable architecture: From 40 tweets to 10,000+ tweets with linear pricing

💰 Pricing: Transparent Event-Based Twitter Scraper Costs

Apidojo's Twitter profile scraper uses transparent pay-per-use pricing—no subscriptions, no hidden fees, no monthly minimums. Extract tweets, replies, and engagement data from Twitter profiles with crystal-clear costs calculated per profile query and per item.

Pricing Structure

Query Type	Base Cost	What's Included	Best For
🐦 Profile Query	$0.016 per profile	40 FREE tweets (2 pages)	Tweet extraction, profile analysis, brand monitoring
💬 Reply Query	$0.016 per reply query	40 FREE replies (2 pages)	Sentiment analysis, conversation tracking, viral content research
📊 Dataset Items	$0.0004 per item	Each additional tweet/reply	Large-scale extraction, comprehensive research projects

How Pricing Works

Profile Scraping (Most Common Use Case): When you scrape a Twitter profile using twitterHandles or startUrls, you pay $0.016 per profile—and the first 40 tweets are completely free. Additional tweets beyond 40 cost $0.0004 each. Perfect for social media monitoring and competitive intelligence.

Reply Thread Extraction: When you enable getReplies, each tweet meeting your minReplyCount threshold triggers a Reply Query at $0.016—and the first 40 replies are completely free. Additional replies beyond 40 cost $0.0004 each. Ideal for sentiment analysis and viral content research.

Date Range Filtering: Use start and end parameters (formats: 2025-10-10 or 2025-11-06_07:00:59_UTC) to extract tweets from specific time periods. You still pay the base $0.016 profile query, but only extract relevant tweets—reducing total costs for campaign-specific analysis.

💵 Real-World Twitter Scraper Pricing Examples

Basic Profile Scraping Scenarios (Includes 40 FREE Tweets Per Profile)

Use Case	Profiles	Tweets Per Profile	Total Cost	Cost Per Tweet
Small test run	1 profile	40 tweets	$0.016	$0.0004
Single deep-dive	1 profile	100 tweets	$0.040	$0.0004
Competitor analysis	1 profile	500 tweets	$0.200	$0.0004
Multi-brand monitoring	5 profiles	40 tweets each	$0.080	$0.0004
Campaign research	5 profiles	100 tweets each	$0.200	$0.0004
Large-scale tracking	10 profiles	200 tweets each	$0.704	$0.00035

Calculation: (profiles × $0.016) + ((total tweets - (profiles × 40 free)) × $0.0004)

Reply Extraction Scenarios (Advanced Use Cases)

Use Case	Configuration	Total Cost	Breakdown
Viral tweet analysis	1 profile, 50 tweets, 5 tweets with 50 replies each	$0.104	$0.016 (profile) + $0.004 (10 extra tweets) + $0.080 (5 reply queries) + $0.004 (10 extra replies)
Brand sentiment tracking	1 profile, 100 tweets, 10 tweets with 100 replies each	$0.304	$0.016 + $0.024 (60 tweets) + $0.160 (10 reply queries) + $0.024 (60 replies)
Influencer engagement study	3 profiles, 80 tweets each, 20 tweets with 60 replies each	$0.512	$0.048 (3 profiles) + $0.048 (120 tweets) + $0.320 (20 reply queries) + $0.016 (40 replies)
Crisis monitoring	1 profile, 200 tweets, 30 tweets with 150 replies each	$1.144	$0.016 + $0.064 (160 tweets) + $0.480 (30 reply queries) + $0.132 (330 replies)

Date-Filtered Campaign Analysis

Use Case	Configuration	Total Cost	Why It's Efficient
Product launch tracking	1 profile, tweets from Oct 1-7, ~80 tweets	$0.032	Date filtering extracts only relevant period
Event monitoring	5 profiles, tweets from specific week, ~60 tweets each	$0.128	Focused extraction reduces unnecessary data costs
Quarterly review	10 profiles, Q3 tweets only, ~150 tweets each	$0.600	Precise date ranges = precise costs

💡 Cost Optimization Tips

Maximize Your FREE Quotas:

• Each profile query includes 40 tweets FREE ($0.016 value)
• Each reply query includes 40 replies FREE ($0.016 value)
• Use maxItems to cap total extraction and control costs

Use Date Filtering Strategically:

• Extract only tweets from relevant time periods (product launches, campaigns, events)
• Reduce total item counts by filtering out irrelevant dates
• Supports both 2025-10-10 and 2025-11-06_07:00:59_UTC formats

Control Reply Extraction Costs:

• Set minReplyCount to only extract replies from high-engagement tweets
• Disable getReplies if you only need tweet content
• Each reply query costs $0.016 but includes 40 replies FREE

Smart Bulk Processing:

• Process multiple profiles simultaneously with predictable per-profile costs
• First 40 tweets per profile are always FREE
• Linear, transparent pricing scales perfectly for agency work

🆓 Demo Mode & Free Users

If you run on Apify's Free plan, you can still use this actor with limited results. The first 40 tweets from each profile cost only $0.016, making it perfect for testing and small social media research projects.

For unrestricted usage and higher quotas, subscribe to a paid Apify plan at apify.com/pricing.

---

📊 Quick Pricing Reference

Base Costs:
✅ Profile Query: $0.016 (includes 40 FREE tweets)
✅ Reply Query: $0.016 (includes 40 FREE replies)
✅ Extra Items: $0.0004 per tweet/reply

Common Scenarios:
- 1 profile, 40 tweets: $0.016
- 1 profile, 100 tweets: $0.040
- 5 profiles, 100 tweets each: $0.200
- 1 profile with replies (50 tweets, 5×50 replies): $0.104

🧾 Twitter Profile Scraper Input Parameters

Field	Type	Description	Default
startUrls	array	Twitter profile URLs to scrape (e.g., https://x.com/elonmusk, twitter.com/taylorswift13). Uses Profile Query pricing ($0.016 per URL, first 40 tweets FREE).	[]
twitterHandles	array	Twitter usernames without @ symbol (e.g., elonmusk, taylorswift13). Uses Profile Query pricing ($0.016 per handle, first 40 tweets FREE).	[]
start	string	Start date for filtering tweets. Supports formats: 2025-10-10 or 2025-11-06_07:00:59_UTC. Perfect for campaign analysis.	null
end	string	End date for filtering tweets. Supports formats: 2025-10-10 or 2025-11-06_16:59:59_UTC. Extract specific time periods.	null
getReplies	boolean	Enable to scrape replies to tweets. Each qualifying tweet triggers a Reply Query ($0.016, first 40 replies FREE). Ideal for sentiment analysis.	false
minReplyCount	integer	Minimum replies a tweet must have before its replies are scraped. Set higher to focus on viral content only.	0
maxItems	integer	Maximum total tweets/replies to output across entire run. Controls your total costs precisely.	Infinity
customMapFunction	string	JavaScript function to transform each output item. Calculate engagement rates, normalize text, or filter fields. More details in Custom Map Function section.	null

---

💡 Twitter Scraper Input Strategy Guide

Choose the right extraction method to optimize costs and get exactly the Twitter data you need. Each approach—username-based scraping, URL extraction, or date-filtered analysis—serves different use cases for this Twitter profile scraper.

---

🎯 Strategy 1: Basic Profile Tweet Extraction

Best for: Brand monitoring, competitor tracking, influencer content analysis, social media research

Method: Username-based extraction (includes 40 FREE tweets per profile)

{
  "twitterHandles": ["nike", "adidas", "puma"],
  "maxItems": 150
}

Cost Component	Calculation	Amount
3 profile queries	3 × $0.016	$0.048
30 additional tweets	(150 - 120 free) × $0.0004	$0.012
Total Cost		$0.060
Cost per tweet		$0.0004

What you get:

• ✅ 150 tweets from Nike, Adidas, and Puma
• ✅ Full engagement metrics (likes, retweets, replies, views)
• ✅ Author profiles, timestamps, media URLs
• ✅ Perfect for competitive social media analysis

Why this works: Each profile query includes 40 free tweets (120 total free!), making multi-brand Twitter username scraping extremely cost-effective.

---

🎯 Strategy 2: Campaign-Specific Date Range Analysis

Best for: Product launch tracking, event monitoring, crisis management, quarterly reviews

Method: Date-filtered extraction with precise time periods

{
  "startUrls": ["https://x.com/taylorswift13"],
  "start": "2025-10-01",
  "end": "2025-10-31",
  "maxItems": 100
}

Cost Component	Calculation	Amount
1 profile query	1 × $0.016	$0.016
60 additional tweets	(100 - 40 free) × $0.0004	$0.024
Total Cost		$0.040
Cost per tweet		$0.0004

What you get:

• ✅ All tweets from October 2025 only
• ✅ Focused extraction reduces unnecessary data
• ✅ Perfect for campaign performance measurement
• ✅ Supports both standard (2025-10-10) and UTC (2025-11-06_07:00:59_UTC) formats

Why this works: Date filtering extracts only relevant tweets, reducing total costs while providing precise campaign insights. Ideal for Twitter data extraction during specific events.

---

🎯 Strategy 3: Viral Content & Reply Analysis

Best for: Sentiment analysis, viral content research, community engagement tracking, crisis monitoring

Method: Tweet extraction with reply thread scraping

{
  "twitterHandles": ["elonmusk"],
  "getReplies": true,
  "minReplyCount": 10,
  "maxItems": 200
}

Cost Component	Calculation	Amount
1 profile query	1 × $0.016	$0.016
10 additional tweets	(50 tweets - 40 free) × $0.0004	$0.004
5 reply queries	5 tweets × $0.016 (40 replies each FREE)	$0.080
50 additional replies	(250 total - 200 free) × $0.0004	$0.020
Total Cost		$0.120

What you get:

• ✅ 50 tweets from Elon Musk's profile
• ✅ Reply threads from 5 high-engagement tweets (10+ replies each)
• ✅ 250 total replies with author info and engagement data
• ✅ Perfect for understanding audience sentiment and viral conversations

Why this works: minReplyCount filters for high-engagement content only, ensuring you extract meaningful discussions. Each reply query includes 40 free replies—ideal for Twitter sentiment analysis.

---

🎯 Strategy 4: Large-Scale Multi-Profile Monitoring

Best for: Agency reporting, industry analysis, influencer tracking, competitive intelligence at scale

Method: Bulk username extraction with controlled limits

{
  "twitterHandles": [
    "nike", "adidas", "puma", "underarmour", "newbalance",
    "reebok", "asics", "skechers", "vans", "converse"
  ],
  "maxItems": 500,
  "getReplies": false
}

Cost Component	Calculation	Amount
10 profile queries	10 × $0.016	$0.160
100 additional tweets	(500 - 400 free) × $0.0004	$0.040
Total Cost		$0.200
Cost per profile		$0.020

What you get:

• ✅ 500 tweets across 10 sportswear brands
• ✅ 400 tweets completely free (40 per profile × 10 profiles)
• ✅ Comprehensive competitive intelligence dataset
• ✅ Perfect for industry benchmarking and trend analysis

Why this works: Bulk processing with generous free quotas makes Twitter profile scraping at scale incredibly affordable—$0.020 per brand including 40 tweets each.

---

🎯 Strategy 5: Time-Sensitive Event Monitoring

Best for: Live event tracking, breaking news analysis, real-time brand monitoring, conference coverage

Method: Short date range with high reply engagement

{
  "twitterHandles": ["techcrunch"],
  "start": "2025-11-20_00:00:00_UTC",
  "end": "2025-11-20_23:59:59_UTC",
  "getReplies": true,
  "minReplyCount": 5,
  "maxItems": 300
}

Cost Component	Calculation	Amount
1 profile query	1 × $0.016	$0.016
10 additional tweets	(50 tweets - 40 free) × $0.0004	$0.004
8 reply queries	8 tweets × $0.016	$0.128
120 additional replies	(440 total - 320 free) × $0.0004	$0.048
Total Cost		$0.196

What you get:

• ✅ All TechCrunch tweets from November 20, 2025
• ✅ Reply threads from 8 high-engagement posts
• ✅ 440 total replies for sentiment analysis
• ✅ Complete conversation context for breaking tech news

Why this works: UTC timestamp precision (2025-11-06_07:00:59_UTC) captures exact time windows—perfect for live event coverage and real-time Twitter data extraction.

---

🎯 Strategy 6: Custom Data Transformation Workflow

Best for: Data pipeline integration, custom analytics, CRM enrichment, engagement rate calculation

Method: Profile extraction with custom map function

{
  "twitterHandles": ["garyvee", "neilpatel", "randfish"],
  "maxItems": 150,
  "customMapFunction": "(object) => ({ ...object, text: object.text?.toUpperCase(), engagementRate: ((object.likeCount + object.retweetCount) / object.viewCount * 100).toFixed(2), totalEngagement: object.likeCount + object.retweetCount + object.replyCount, media: undefined })"
}

Cost Component	Calculation	Amount
3 profile queries	3 × $0.016	$0.048
30 additional tweets	(150 - 120 free) × $0.0004	$0.012
Total Cost		$0.060

What you get:

• ✅ 150 marketing expert tweets with custom transformations
• ✅ Calculated engagement rates for each tweet
• ✅ Normalized text (uppercase) and computed metrics
• ✅ Cleaned output ready for database import

Why this works: Custom map function transforms data during extraction—no post-processing needed. Perfect for Twitter account scraper workflows requiring specific output formats.

---

📊 Strategy Comparison Table

Strategy	Best For	Profiles	Tweets	Replies	Total Cost	Cost/Profile
Basic Extraction	Brand monitoring	3	150	0	$0.060	$0.020
Date-Filtered	Campaign tracking	1	100	0	$0.040	$0.040
Viral + Replies	Sentiment analysis	1	50	250	$0.120	$0.120
Large Multi-Profile	Industry analysis	10	500	0	$0.200	$0.020
Event Monitoring	Live coverage	1	50	440	$0.196	$0.196
Custom Transform	Data pipelines	3	150	0	$0.060	$0.020

---

🧠 Pro Tips for Twitter Extractor Optimization

✅ Maximize Free Tweet Quotas

Each profile query includes 40 FREE tweets ($0.016 value). Scraping 10 profiles = 400 free tweets before paying for additional items.

✅ Use Date Filtering Strategically

Extract only tweets from relevant time periods (product launches, campaigns, quarterly reviews). Reduces total item counts and controls costs precisely.

✅ Control Reply Extraction Costs

• Set minReplyCount higher (e.g., 10+) to only extract replies from viral content
• Disable getReplies: false if you only need tweet content
• Each reply query includes 40 free replies—use strategically for high-value conversations

✅ Set maxItems for Budget Control

Calculate your exact budget: maxItems = (budget - (profiles × $0.016)) / $0.0004 + (profiles × 40)

✅ Batch Related Profiles

Scrape multiple related accounts in one run (competitors, industry leaders, influencers) to maximize efficiency and minimize overhead.

✅ Custom Map Function for Efficiency

Transform data during extraction rather than post-processing. Calculate engagement rates, normalize text, filter fields—all in real-time.

---

📦 Output

Output is stored in a dataset. Each item represents a comprehensive tweet or reply record with full engagement metrics and author details.

Full Tweet Output

{
  "type": "tweet",
  "id": "1970912731290058851",
  "url": "https://x.com/taylorswift13/status/1970912731290058851",
  "twitterUrl": "https://twitter.com/taylorswift13/status/1970912731290058851",
  "text": "A showgirl knows to save some of her best tricks for the grand finale…",
  "fullText": "A showgirl knows to save some of her best tricks for the grand finale…",
  "source": "Twitter for iPhone",
  "retweetCount": 34399,
  "replyCount": 4152,
  "likeCount": 190278,
  "quoteCount": 7463,
  "viewCount": 7901648,
  "createdAt": "Wed Sep 24 18:06:27 +0000 2025",
  "lang": "en",
  "bookmarkCount": 5363,
  "isReply": false,
  "conversationId": "1970912731290058851",
  "author": {
    "userName": "taylorswift13",
    "name": "Taylor Swift",
    "id": "17919972",
    "isVerified": false,
    "isBlueVerified": true,
    "profilePicture": "https://pbs.twimg.com/profile_images/1970913468283817984/zGEQHGi9_normal.jpg",
    "description": "And, baby, that's show business for you.",
    "followers": 93071499,
    "following": 0
  },
  "media": [
    "https://pbs.twimg.com/media/G1oWrA9W0AA49ys.jpg",
    "https://pbs.twimg.com/media/G1oWrA-WQAAqmaK.jpg"
  ],
  "entities": {
    "hashtags": [],
    "urls": [],
    "user_mentions": []
  }
}

Reply Output

{
  "type": "reply",
  "id": "1970913821093847392",
  "url": "https://x.com/swiftie_forever/status/1970913821093847392",
  "text": "THIS IS EVERYTHING!! 😭💕",
  "retweetCount": 234,
  "replyCount": 18,
  "likeCount": 3421,
  "viewCount": 54823,
  "createdAt": "Wed Sep 24 18:10:15 +0000 2025",
  "isReply": true,
  "conversationId": "1970912731290058851",
  "inReplyToStatusId": "1970912731290058851",
  "author": {
    "userName": "swiftie_forever",
    "name": "Swiftie Forever 💕",
    "followers": 12453,
    "following": 892
  }
}

Output Fields Explained

Field	Description
type	"tweet" for original tweets, "reply" for replies to tweets
id	Unique Twitter status ID
url	Direct link to tweet on x.com
twitterUrl	Direct link to tweet on twitter.com
text	Tweet text content (may be truncated)
fullText	Complete tweet text without truncation
retweetCount	Number of retweets/reposts
replyCount	Number of replies to this tweet
likeCount	Number of likes/favorites
quoteCount	Number of quote tweets
viewCount	Total tweet views/impressions
bookmarkCount	Number of bookmarks
createdAt	Tweet timestamp (UTC format)
lang	Detected language code (e.g., "en", "es")
source	Device/app used to post (e.g., "Twitter for iPhone")
conversationId	ID of the conversation thread
isReply	Boolean indicating if this is a reply
inReplyToStatusId	ID of parent tweet (for replies only)
author.userName	Twitter username/handle
author.name	Display name
author.id	Unique user ID
author.isVerified	Legacy verification status
author.isBlueVerified	Twitter Blue verification status
author.profilePicture	Profile picture URL
author.description	User bio text
author.followers	Follower count
author.following	Following count
media	Array of media URLs (images, videos)
entities.hashtags	Array of hashtags used in tweet
entities.urls	Array of URLs mentioned in tweet
entities.user_mentions	Array of @mentioned users

Export Formats & Access Methods

Download Options:

• JSON (native format, most detailed)
• CSV (spreadsheet-ready, flattened structure)
• Excel (.xlsx with proper formatting)
• XML (structured data export)
• RSS (feed format for monitoring)

Access Methods:

• Web UI: Download directly from dataset storage tab
• Apify API: Programmatic access via REST API
• Client Libraries: Python, JavaScript, PHP integration
• Webhooks: Real-time notifications on run completion
• Integrations: Direct export to Google Sheets, Make, Zapier

---

🧩 Custom Map Function

You can use this function to transform the output of each tweet or reply. This function receives each item as an argument, allowing you to modify formatting, add computed fields, or filter attributes.

The return value must be an object. You can:

• Add new fields: Return fields not in the default output
• Modify existing fields: Transform values (e.g., uppercase text, calculate rates)
• Remove fields: Set unwanted fields to undefined

Example Function:

(object) => ({
  ...object,
  text: object.text?.toUpperCase() || null,
  engagementRate: ((object.likeCount + object.retweetCount) / object.viewCount * 100).toFixed(2),
  authorName: object.author?.name,
  totalEngagement: object.likeCount + object.retweetCount + object.replyCount + object.quoteCount,
  media: undefined
})

Input:

{
  "type": "tweet",
  "id": "1970912731290058851",
  "text": "A showgirl knows to save some of her best tricks for the grand finale…",
  "retweetCount": 34399,
  "likeCount": 190278,
  "viewCount": 7901648,
  "author": {
    "name": "Taylor Swift"
  },
  "media": ["https://example.com/image.jpg"]
}

Output:

{
  "type": "tweet",
  "id": "1970912731290058851",
  "text": "A SHOWGIRL KNOWS TO SAVE SOME OF HER BEST TRICKS FOR THE GRAND FINALE…",
  "retweetCount": 34399,
  "likeCount": 190278,
  "viewCount": 7901648,
  "author": {
    "name": "Taylor Swift"
  },
  "engagementRate": "2.85",
  "authorName": "Taylor Swift",
  "totalEngagement": 236292
}

Use the customMapFunction parameter to transform output during extraction:

Example: Calculate Engagement Metrics

(object) => ({
  ...object,
  engagementRate: ((object.likeCount + object.retweetCount) / object.viewCount * 100).toFixed(2),
  totalEngagement: object.likeCount + object.retweetCount + object.replyCount + object.quoteCount,
  viralScore: (object.retweetCount * 2 + object.likeCount + object.replyCount * 3) / object.viewCount * 1000
})

Example: Normalize Text & Remove Media

(object) => ({
  ...object,
  text: object.text?.toUpperCase().trim(),
  authorName: object.author?.name,
  media: undefined,
  entities: undefined
})

Example: Filter for High Engagement Only

(object) => {
  if (object.likeCount < 100) return null;
  return {
    id: object.id,
    text: object.text,
    likes: object.likeCount,
    author: object.author?.userName
  };
}

Result: Cleaner datasets optimized for your specific workflow—no post-processing required!

🎎 Who Needs This?

This Twitter profile scraper is built for anyone who needs fast, affordable, Twitter/X data extraction with transparent pricing and structured output.

Social Media Managers & Brand Marketers
Use the Twitter profile scraper for brand monitoring, competitor analysis, launch tracking, and reporting — starting at just $0.016 per profile with 40 tweets included. Perfect for turning Twitter timelines into clean datasets for dashboards, weekly reports, and campaign reviews.

SEO, Content & Growth Teams
Extract Twitter data to discover content ideas, track topic trends, and monitor industry conversations. Use tweet exports for topical authority, E-E-A-T research, and to feed content calendars with real audience language and search intent.

Data, Analytics, AI & LLM Teams
Treat this as a low-friction Twitter data pipeline. Collect structured tweets and replies for sentiment analysis, trend detection, LLM fine-tuning, RAG corpora, and custom scoring models — all with predictable, event-based pricing and no proxy hassle.

Product, Growth, RevOps & BizOps Teams
Pipe Twitter profile and engagement data into internal tools, CRMs, and BI dashboards. Build alerting, churn/retention signals, or feature feedback loops powered by real conversations from customers, users, and competitors.

Agencies, Freelancers & Consultants
Use the scraper to power client social media reports, competitor benchmarks, and influencer lists. You get clear per-profile costs and structured JSON/CSV/Excel output, so you can plug Twitter data directly into your reporting workflows without building your own scraper.

Startups, Indie Hackers & Small Businesses
Get competitive intelligence and lightweight social listening without committing to expensive enterprise tools. For a few cents per profile, you can track your own account, your competitors, and key partners.

Influencer & Creator Marketing Teams / Platforms
Scrape creator profiles to track posting frequency, content themes, and engagement metrics at scale. Use the Twitter account scraper to score influencers, monitor campaigns, and analyze audience sentiment — with pricing that scales from a handful of profiles to large creator lists.

Researchers, Academics & Journalists
Collect Twitter/X datasets for research, case studies, and articles. Export tweets and replies with timestamps, language, and engagement metrics to study online discourse, events, and communities in a reproducible way.

Twitter Scraper Export

📤 Twitter Scraper Export
During the run, the actor stores results into a dataset. Each item is a separate tweet or reply. You can manage the results in any language (Python, PHP, Node.js/NPM). See the FAQ or our API reference to learn more about getting results from this Twitter Profile Scraper actor.

Export formats include:

• JSON
• CSV
• Excel
• XML
• RSS

Access data via:

• Web UI download
• Apify API
• Client libraries (Python, JavaScript, PHP, etc.)

🔧 Troubleshooting

• Getting fewer results than expected? Increase maxItems or adjust your date range. Remember: first 40 tweets per profile are FREE!
• Unexpected costs? Each profile query costs $0.016 (includes 40 tweets). Each reply query costs $0.016 (includes 40 replies). Additional items cost $0.0004 each.
• Missing outputs? Open the Storage tab to explore/download full datasets.
• No results? Check your twitterHandles/startUrls, and verify the date range (start/end) is correct. Supports both 2025-10-10 and 2025-11-06_07:00:59_UTC formats.
• Want to minimize costs? Use fewer profiles, set a lower maxItems, or disable getReplies to control spending.
• Replies not showing? Ensure getReplies is set to true and check that tweets meet the minReplyCount threshold.
• Date format issues? Both standard format (2025-10-10) and UTC format (2025-11-06_07:00:59_UTC) are supported.

📞 Contact

If you need any sort of support, please send an email to apidojo10@gmail.com. You name it, we get it.

## What Is a Twitter Profile Scraper?

A Twitter profile scraper is a tool that pulls structured data from Twitter/X profiles so you don’t have to do it manually. Instead of scrolling timelines and copy-pasting, you get clean records of:

• Tweet text

• Engagement metrics (likes, retweets, replies, views)

• User info (bio, followers, verification, etc.)

• Conversation threads and reply chains

This kind of Twitter data extraction is the backbone of social listening, brand monitoring, competitor research, and sentiment analysis. You can see which tweets perform well, how people react to announcements, and what topics keep coming up around your brand or niche.

Used well, a Twitter profile scraper helps you:

• Build and refine your social media and content strategy

• Track competitors and industry leaders over time

• Measure audience sentiment around launches, crises, and campaigns

• Collect high-quality text data for models, dashboards, or research

Whether you’re a social media manager, a marketer, a researcher, or a developer wiring Twitter data into your product, a profile scraper gives you consistent, machine-readable data instead of screenshots and guesses.

---

Features of Our Twitter Profile Scraper

This Twitter/X profile scraper is built for people who care about reliable data, predictable costs, and easy integration.

Transparent, Event-Based Pricing

You only pay for what you actually extract:

• $0.016 per profile query – includes the first 40 tweets for free

• $0.0004 per additional tweet or reply

If you turn on reply extraction, each reply query also includes 40 replies in the base price. That makes it cheap enough for everyday brand monitoring and big enough for serious research.

Flexible Time Windows & Tweet Filtering

You can decide exactly which tweets to pull:

• Filter by date range using either 2025-10-10 or 2025-11-06_07:00:59_UTC

• Limit total items with maxItems

• Focus only on recent content, campaigns, or events

This keeps your Twitter data extraction relevant and your costs under control.

Customizable Output (Custom Map Function)

Every tweet and reply goes through an optional custom map function:

• Add metrics like engagement rate, viral score, or sentiment bucket

• Normalize fields (e.g., text cleanup, language filtering)

• Remove fields you don’t care about to keep datasets lean

You end up with LLM-ready or dashboard-ready data without an extra cleaning step.

No Proxies, No Cookies, No Drama

The scraper works without proxy setup or authentication:

• No cookie juggling

• No residential proxy bills

• No separate infrastructure to maintain

You just pass input, run, and download your dataset.

Reply & Conversation Extraction

You can optionally pull full reply threads for deeper analysis:

• Configure minReplyCount to only follow high-engagement tweets

• Extract replies with full author + engagement data

• Use it for sentiment analysis, crisis tracking, or community research

If you just want top-level tweets, disable replies and keep things lean. If you want to understand conversations, turn it on and get the full context.

---

Input Parameters for Twitter Profile Scraping

You control how and what the scraper collects using a small set of input fields.

Core Inputs

• startUrls
  List of Twitter/X profile URLs, e.g.
  https://x.com/elonmusk or https://twitter.com/taylorswift13.
  Each URL triggers a Profile Query ($0.016, first 40 tweets included).

• twitterHandles
  Usernames without the @, e.g. elonmusk, taylorswift13.
  Works the same as startUrls but is more convenient for bulk lists.

Time & Volume Control

• start / end
  Optional date filters to limit tweets to a specific period.
  Supports:

  • 2025-10-10

  • 2025-11-06_07:00:59_UTC
    Ideal for product launches, campaigns, events, or quarterly reviews.

• maxItems
  Hard cap on the total number of tweets + replies returned across the whole run.
  Use this to enforce a budget or prevent accidental “infinite scroll”.

Replies & Conversations

• getReplies
true / false. When enabled, the scraper fetches replies to tweets that meet your minReplyCount threshold. Each such tweet triggers a Reply Query ($0.016, first 40 replies included).

• minReplyCount
  Minimum number of replies a tweet must have before its replies are scraped.
  Example: set 10 to only follow threads with real traction.

Output Transformation

• customMapFunction
  A JavaScript function (as a string) that receives each tweet/reply object and returns a transformed version. You can:

  • Compute new fields (e.g. engagementRate, totalEngagement)

  • Normalize text for LLMs

  • Strip out media or entities you don’t need

With these inputs, you can keep your Twitter scraping focused, affordable, and aligned with your exact use case instead of dumping everything into a giant, messy dataset.

---

Who Can Benefit From Twitter Profile Scraping?

A good Twitter/X scraper quietly powers a lot of different workflows. Some typical users:

Social Media & Marketing Teams

• Track your own profiles, competitors, and partners

• Measure tweet performance and audience sentiment over time

• Identify content formats and topics that actually move the needle

• Build weekly/monthly reports without manual exports

SEO, Content & Growth

• Mine Twitter/X for topic ideas, questions, and pain points

• Capture real user language for landing pages, blog posts, and FAQs

• Monitor niche conversations to guide content clusters and topical authority

Small Businesses & Startups

• Keep an eye on how people talk about your brand and competitors

• Spot early feedback, complaints, or feature requests

• Do simple social listening without paying enterprise tool prices

Developers & Product Teams

• Pipe structured Twitter data into apps, CRMs, alerts, or dashboards

• Build social listening tools, influencer discovery features, or internal analytics

• Use tweets and replies as labeled data for ML/LLM experiments

Data, Research & Analytics Teams

• Run sentiment analysis on tweets around events or brands

• Study viral patterns, community behavior, or crisis timelines

• Gather reproducible datasets for academic or commercial research

In short: if Twitter/X is part of how you listen, learn, or ship — a Twitter profile scraper gives you a clean data feed instead of a browser tab addiction.

---

Custom Map Function for Advanced Data Processing

The custom map function is where this scraper stops being “just a scraper” and starts acting like a mini data pipeline.

For every tweet or reply, your function runs once and returns the object you actually want stored. That means you can:

• Add fields

  • engagementRate based on likes + retweets + views

  • viralScore combining replies, quotes, and bookmarks

  • Simple sentiment buckets based on keywords

• Modify fields

  • Normalize text (uppercase/lowercase, trim, remove emojis)

  • Shorten text for previews

  • Format dates differently

• Remove fields

  • Drop heavy fields like media or entities if you don’t need them

  • Keep only IDs and metrics for lightweight analytics

Example idea:

(object) => ({ id: object.id, url: object.url, text: object.fullText?.trim(), author: object.author?.userName, createdAt: object.createdAt, totalEngagement: object.likeCount + object.retweetCount + object.replyCount + (object.quoteCount || 0), engagementRate: object.viewCount ? Number(((object.likeCount + object.retweetCount) / object.viewCount * 100).toFixed(2)) : null });

The end result: your dataset comes out already shaped for your dashboard, LLM prompt, or notebook, with no extra cleaning step in between.

---

Start Extracting Twitter Data Today

If you already know which profiles you care about, you’re one input away from having their data in a clean dataset.

With this Twitter profile scraper you get:

• Straightforward pricing:

  • $0.016 per profile (40 tweets included)

  • $0.016 per reply query (40 replies included)

  • $0.0004 per extra tweet or reply

• Simple setup:

  • No proxies

  • No cookies

  • Just handles/URLs, dates, and a few options

• Structured output:

  • JSON by default

  • CSV/Excel/XML/RSS for reporting and tooling

  • Easy to feed into BI tools, scripts, or LLM pipelines

Use it for monitoring, research, dashboards, or training data – whatever your stack looks like. Set your inputs, run the actor, and you’ll have Twitter/X data you can actually work with, not just screenshots and vibes.

❓ Frequently Asked Questions about Twitter Profile Scraping (FAQ)

How to Scrape Twitter Profiles?

Scraping Twitter profiles with our Apify Twitter Profile Scraper actor is straightforward and requires no technical setup. Simply provide Twitter usernames (handles) or profile URLs as input parameters, optionally specify date ranges (start and end dates in either 2025-10-10 or 2025-11-06_07:00:59_UTC format), and run the actor. The scraper will automatically extract tweets and store them in a structured dataset format.

You can customize your scraping by:

• Setting date ranges for tweet filtering with start and end parameters (supports multiple date formats)
• Enabling reply extraction with getReplies
• Setting minimum reply thresholds with minReplyCount
• Limiting total output with maxItems
• Using the custom map function to format your data

The entire process is automated, and results are available immediately after the run completes. No proxy configuration or complex setup is required.

Can You Scrape Twitter Profiles?

Yes, you can absolutely scrape Twitter profiles using our Twitter profile scraper. Our actor is specifically designed to extract tweets, replies, and engagement data from Twitter user profiles efficiently and reliably. Whether you need 40 tweets or 10,000, our scraper handles requests of any size.

The actor supports:

• Username-based scraping: Provide a list of Twitter handles (without @ symbol)
• URL-based scraping: Use direct Twitter profile URLs (x.com or twitter.com)
• Date range filtering: Extract tweets from specific time periods (flexible date formats supported)
• Reply extraction: Get conversation threads with configurable thresholds
• Real-time data extraction: Get current tweets and engagement metrics on demand

With transparent event-based pricing starting at just $0.016 per profile (including the first 40 tweets FREE!), it's both accessible and cost-effective for projects of any scale.

How to Scrape Data from Twitter?

To scrape data from Twitter using our Twitter profile scraper, follow these simple steps:

1. Set Up Your Input

• Provide either twitterHandles (usernames without @) or startUrls (direct Twitter profile URLs)
• Optionally set start and end dates for date range filtering (formats: 2025-10-10 or 2025-11-06_07:00:59_UTC)
• Decide if you want to extract replies by enabling getReplies

2. Configure Your Scraping Parameters

• Set minReplyCount to control which tweets' replies get scraped (only tweets with this many replies or more)
• Use maxItems to limit total output across all profiles
• Add a customMapFunction if you want to transform the output format

3. Run the Actor

• Launch the actor on the Apify platform
• Monitor progress in real-time through the run console
• Access results immediately in the dataset storage

4. Export Your Data

• Download results in JSON, CSV, Excel, or other formats
• Access data programmatically via the Apify API
• Integrate with your existing workflows and tools

The output includes structured data with fields like id, text, createdAt, author, likeCount, retweetCount, replyCount, viewCount, and url for each tweet, making it ready for immediate analysis or integration.

Pricing Transparency:

• Profile queries: $0.016 (includes 40 tweets FREE)
• Reply queries: $0.016 (includes 40 replies FREE)
• Additional items: $0.0004 per tweet/reply

What data can the Twitter Profile Scraper extract?

The scraper extracts:

• Tweet text & full text

• Timestamps

• Engagement metrics

  • Likes

  • Retweets

  • Replies

  • Views

  • Quotes

  • Bookmarks

• Author details (username, name, ID, followers/following, bio, profile image, verification flags)

• Media URLs (images/videos)

• Conversation IDs & reply chains

• Language, source app, entities

This makes it suitable for sentiment analysis, dashboards, market research, LLM datasets, and more.

How many tweets can I scrape at once?

As many as you need.
The scraper supports:

• Single profiles

• Bulk list of handles

• Multi-brand monitoring

• Scaling up to thousands of tweets per profile

• Scaling across hundreds of profiles in one run

You can limit output with maxItems for cost control.

Can it extract replies and conversation threads?

Yes. Enable getReplies to fetch replies for each tweet that meets the minReplyCount threshold.

• Each reply query includes 40 free replies

• Additional replies cost $0.0004 each

This is ideal for:

• Sentiment analysis

• Crisis detection

• Viral content research

• Community engagement tracking

Start scraping Twitter data today and unlock valuable insights for your social media strategy! 🚀