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Detect customer complaints with Twitter search

Find public brand complaints containing common problem signals such as bugs, outages, broken features, or support issues.

Try for free
X (Twitter) Tweet Scraper | $0.00015/Tweet | Pay-Per-Result
X (Twitter) Tweet Scraper | $0.00015/Tweet | Pay-Per-Resultxquik/x-tweet-scraper
Text
Tweet URL
Author
Author username
+20 fields
Text
Number
Boolean
List
Object

Input

Search terms:@NotionHQ (broken OR bug OR issue OR outage OR support) lang:en -from:NotionHQ
Sort by:Latest
Max items:1000
Output variant:rich

Output fields

Text
Tweet URL
Author
Author username
Tweet ID
Created at
Likes
Replies
Retweets
Quotes
Views
Bookmarks
Media URLs
Language
Retweet time
Status
Message
Actor version
Result type
Reply coverage
Source Tweet ID
Source target
Engagement mode
Search term

How it works

Sign up on Apify or log in

The X (Twitter) Tweet Scraper | $0.00015/Tweet | Pay-Per-Result Actor is ready to run with the inputs already set for "Detect customer complaints with Twitter search". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Detect customer complaints with Twitter search" task

The X (Twitter) Tweet Scraper | $0.00015/Tweet | Pay-Per-Result Actor will start running based on the input automatically. You can also change all the input fields, like search terms, sort by, and more, to match your specific use case.

Receive the "Detect customer complaints with Twitter search" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as text, tweet url, author, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Detect customer complaints with Twitter search" task via API.

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Integrate "Detect customer complaints with Twitter search" into your workflow

Connect "Detect customer complaints with Twitter search" with 100+ integrations, or run it via API or MCP.

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