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Build a Sentiment Dataset by Date Range
Created by
ВAH
Builds a topic dataset from X (Twitter) for sentiment analysis. Set This_exact_phrase (here 'customer service') and a start/end date, and the scraper collects matching tweets day by day with 55 fields each: fullText, language, engagement, author stats and timestamps. Feed the text and metrics into sentiment and NLP pipelines. Export to CSV or JSON.
Ultimate X (Twitter) Advanced Search Scraperdelicious_zebu/ultimate-x-twitter-advanced-search-scraper
Tweet URL
Created At
Author Handle
Author Name
+51 fieldsTextNumberBooleanListObject
Input
This exact phrase:customer service
Start date (optional):2026-08-01
End date (optional):2026-08-31
Sort by (Top / Latest):Latest
Split mode(required):day
Language(required):en
Max items (per search):80
Output fields
Tweet URL
Created At
Author Handle
Author Name
Author Followers
Verified
Verified Type
Text
Likes
Reposts (RT+Quote)
Retweets
Quotes
Replies
Views
Bookmarks
Hashtags
Mentions
Image URLs
Video URLs
External URLs
Cashtags
Language
Is Reply
Is Retweet
Is Quote
Is Ad
Possibly Sensitive
Conversation ID
Tweet ID
In-Reply-To Handle
In-Reply-To Name
In-Reply-To URL
In-Reply-To Tweet ID
Quoted Tweet URL
Quoted Tweet ID
Quoted Text
Quoted Author Handle
Card Title
Card Description
Card Domain
Source App
Author ID
Author URL
Author Website
Author Bio
Author Location
Author Following
Author Tweet Count
Author Likes Given
Author Listed Count
Author Media Count
Author Created At
Author Profile Image
Query String
Search URL
Sign up on Apify01
Create your Apify account to access the Ultimate X (Twitter) Advanced Search Scraper.
Start the run02
The Actor will start running based on the input automatically.
Receive the output03
Monitor the progress in real-time. You will be notified as soon as your dataset is complete and ready for review.
Integrate into your workflow04
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow.
