Extract tweets by keyword or hashtag, scrape Twitter profiles in bulk, and monitor trending conversations — without touching the Twitter API. Specrom's scraper handles anti-bot evasion, proxy rotation, and data normalization. You get clean, structured data delivered as CSV or via REST API.
// Tweet record — Specrom Twitter Scraper { "tweet_id": "1879234560012345", "text": "Excited to announce our Series A. Huge thanks to the team 🚀 #startup #fintech", "created_at": "2025-01-14T09:22:11Z", "likes": 847, "retweets": 203, "replies": 61, "views": 42100, "hashtags": ["startup", "fintech"], "author": { "username": "jamespatel", "followers_count": 18400, "verified": false }, "is_retweet": false, "language": "en" }
Every tweet record includes the engagement metrics, author details, and structural metadata you need for analysis — without the cleaning overhead of raw API responses. Same schema across every query.
// Full tweet record fields
tweet_id, text, created_at,
likes, retweets, replies,
quotes, views, language,
is_retweet, is_reply, is_quote,
parent_tweet_id,
hashtags[], mentions[],
urls[], media_type, media_url,
author_username, author_display_name,
author_followers, author_following,
author_tweet_count, author_verified,
author_joined_date,
tweet_url
Depending on your use case, you can pull tweets by keyword, scrape a specific account's timeline, extract profile data in bulk, or set up a recurring keyword monitor. Tell us what you need and we'll match the right method.
Keywords, hashtags, usernames, or a combination. Specify date range for historical pulls, or set up real-time / near-real-time collection. Filters for language, min engagement, and verified accounts available.
Our infrastructure handles rotating proxies, anti-bot evasion, pagination, and deduplication. Tweets and profiles are validated and normalized before delivery — no raw API noise.
CSV or Parquet for bulk pulls. JSON via REST API for real-time integration. Push to S3, SFTP, database, or webhook. For recurring monitors, only new tweets since the last run are included in each delivery.
Twitter/X is one of the highest signal-to-noise data sources available for real-time market intelligence. Here's how different teams use it.
Track mentions of your brand, competitors, or product categories. Get structured engagement data so you can measure share of voice, spot sentiment shifts, and catch PR events before they escalate.
Pull large historical datasets on a topic — months of tweets mentioning a technology, market, or trend — and analyse engagement patterns, key voice identification, and narrative evolution over time.
Collect domain-specific Twitter conversations for LLM fine-tuning, sentiment model training, or NLP dataset construction. Structured tweet data with engagement labels and author metadata included.
Social scientists, communication researchers, and political analysts need Twitter data at scale. Specrom delivers structured datasets reproducible enough for citation — with defined scrape dates and consistent schema.
Twitter's API restructure in 2023 effectively priced out most independent developers, researchers, and mid-sized businesses. The free tier at 1,500 tweets per month is insufficient for any serious data use case. Basic access at $100/month gives 10,000 tweets monthly with no historical search. That's not a research tool; it's a rate-limited preview.
The Pro tier, where full-archive search and meaningful volume becomes available, starts at $5,000 per month. For a startup, an academic team, or a small analytics firm, that's simply not a viable path to Twitter data.
The result is that the majority of real-world Twitter data use cases such as brand monitoring, market research, training data collection, social science research are now being served by third-party data providers who built infrastructure before the API changes and continue to maintain access at scale.
// Twitter API v2 — Basic tier // $100/month = 10,000 tweets // Historical search: NOT included // Full-archive: Pro tier only ($5K/mo) // Specrom — same data, different model GET /tweets/search ?q="fintech startup" &from=2024-01-01 &to=2024-12-31 &lang=en &min_likes=10 // Returns structured tweets: { "total": 84320, "tweets": [ /* 20+ fields each */ ] }
Tweets (by keyword, hashtag, or user timeline), user profiles (bulk profile data extraction), follower and following lists, and trending topic data. For each data type, we return structured records with all available public fields — not just the subset the official API exposes in its lower tiers.
Historical availability depends on the query. For popular keyword and hashtag searches, we can typically pull back 12–18 months of data. For specific user timelines, up to the account's full public history depending on account size. Contact us to confirm availability for your specific query before ordering.
No. Specrom's infrastructure handles Twitter access independently. You don't need to register a Twitter developer account, apply for API access, or manage credentials.
CSV or Parquet for bulk one-time pulls, delivered by email, S3, or SFTP. JSON via REST API for real-time or recurring integrations. Webhook delivery available for event-triggered workflows.
Yes. Our keyword monitoring service runs your search on a daily, weekly, or monthly cadence and delivers only new tweets since the last pull. Delta delivery keeps your pipeline lean and avoids processing duplicates.
Brandwatch and similar tools are analytics platforms with dashboards and reporting built in. Specrom is a raw data service; you get the underlying structured data, which you can load into your own analytics stack, model, or BI tool. If you need the data itself rather than a pre-built report, Specrom is the right fit.
Describe your query — keywords, hashtags, or accounts — and we'll respond within 24 hours with a sample and a quote.