How to Scrape Twitter Profiles in 2024 [No-Code]

Shehriar Awan
March 27, 2024
7 min read

You’ve got a list of 100k X (previously Twitter) accounts and you want to export their metadata to an Excel spreadsheet. How much time would it take if you do it manually?

We can do it programmatically. All you have to do is understand X’s HTML page structure, find the right elements to target and code a scraper. But not everyone is a nerd.

What if I need a simple solution? Well that’s what we’re going to do. In this article, we’ll learn how to scrape Twitter profiles without writing code.

But why would anyone want to scrape Twitter profiles? Let’s explore some use cases.

Why scrape Twitter profiles?

With 528.3 million monetizable monthly active users and creator monetization initiatives, Twitter has become one of the biggest platforms for content creators.

Scraping Twitter profiles has multiple use cases including:

  1. Influencer Marketing
  2. Audience Segmentation
  3. Competitive Intelligence
  4. Market Research

But is it legal to scrape Twitter profiles data?

Twitter itself discourages scraping. In fact Elon sued Center for Countering Digital Hate and four unknown individuals for scraping Twitter data.

But there’s a catch. In the case of CCDH, X corp alleged that they “embarked on a scare campaign” to drive away advertisers.

Similarly, the four unknown individuals were found flooding the sign up page which resulted in putting a strain on the company’s servers and disrupted users’ experience.

In both cases, the company alleged that scraping practices were harming their platform by driving away advertisers and affecting user experience.

Which brings us to the main point. If I’m scraping publicly available data from Twitter profiles without violating Twitter’s terms, is it legal to scrape Twitter data?

The answer is no. If done without harming the platform in any way, scraping publicly available data is completely legal.

I’ve already covered this in detail, along with some lawsuit references in my article on: How to Scrape Twitter Search Results without coding [2024 Edition]. Do check it out.

But why scrape Twitter if there’s an API available.

Why not use Twitter API?

There are 3 main reasons why Twitter API is not suitable for web scraping data at scale especially if you’re not a technical person.

  1. Too expensive
  2. Limited Tweet cap volumes
  3. Requires coding experience

I’ve explained this already in my article – How to Scrape Tweets from Twitter (No Code) - 2024 Edition. You can check it out for a detailed answer.

Coming back to the main question. If the API is not suitable and I don’t know how to code, how can I scrape Twitter profile data?

Let’s learn how to do it. 🏃

How to scrape Twitter profiles without coding using

We’ll be using Twitter Profile Scraper – the best Twitter scraper for extracting user profile data without API and without coding.

Cool features

  1. 20+ data attributes
  2. 100+ profiles per minute
  3. Cloud-based – no installation required
  4. Schedule feature
  5. Direct export to Google Sheets and Amazon S3
  6. Developer-friendly API


  1. Free: 45000 profiles per month
  2. Pro: €0.09 per 1000 profiles
  3. Business: €0.06 per 1000 profiles
  4. Enterprise: €0.05 per 1000 profiles

Scraping Twitter profiles using - Step by step guide

It takes less than 2 minutes to set up and launch Twitter Profile Scraper. We’ll do the entire web scraping process in 6 very simple steps.

  1. Get profile username/URLs
  2. Create Squid
  3. Add tasks
  4. Adjust behavior
  5. Launch
  6. Enjoy

Let’s go! 💨

Step 1 - Get profile username/URL

With Lobstr, all you need to get started is a Twitter username or profile link.

To grab those, head over to, find the profile you want to scrape, and copy either the username or the profile URL.

For this tutorial, I've already got a list of Twitter profiles ready to go.

Let’s go to the next step.

Step 2 - Create Squid

Now go to your dashboard and create a new Squid. Don’t have an account yet? Create one right now! It’s free.

To create a Squid, click the New Squid button and type ‘Twitter Profile’, select Twitter Profile Scraper and your squid is created.

Now let’s give it the input and adjust some settings.

Step 3 - Add tasks

Next up, click on 'Add tasks'. This is where we'll paste all those Twitter usernames you copied earlier. You can add a bunch at once, no problem.

Got a huge list of usernames? Don't sweat it! Just use the Upload file option and load 'em all in one easy click. That’s what I’m going to do.

Awesome. Now, let's fine-tune how our crawler works. Click Save and we'll jump to the next step.

Step 4 - Adjust behavior

In the basic settings, you decide when to stop the crawler. This is handy if you have a ton of profiles to work through and your daily credits are limited.

By choosing when to end the run, you can spread your daily credits out over several days.

In advanced settings, the first option you get is the JSON button. Toggle this ON if you want the complete, unprocessed Twitter profile data.

This is helpful if you need to do your custom analysis or work with the data in a specific way.

If 100 results per minute feel too slow, you can increase the concurrency for much faster scraping (up to 40x!).

The Unique Results option makes sure you don't get duplicate data, and the No Line Breaks option can be useful if you need to remove line breaks from text in csv output.

Next up, Notifications. You can get email alerts when your scrape is finished successfully, or if there's an error that needs your attention.

Now we’re all set to launch. 🚀

Step 5 - Launch

Let’s initiate the launch sequence. You can manually launch the Twitter scraper. It’ll instantly start collecting data for you.

But what if I need to monitor the growth of these accounts on a monthly basis? We can use the schedule feature for that.

Select repeatedly from the options and set up your launch frequency and schedule. The Twitter profile scraper will automatically run on the time and frequency you’ve chosen.

After finalizing your launch preferences, click Save and tada! We’ve taken off!

Step 6 - Enjoy

Now our Twitter Profiles scraper has started collecting data from the Twitter accounts. At 100 profiles per minute speed, the data collection will take less than 2 minutes to complete.

You can watch live data collection when the scraper is running by going to the Results tab.

Once data extraction completes, you can download the extracted data as a csv file by clicking the Download button. The csv file can be viewed in MS Excel.

But what if I need to export this data to Google Sheet? You can export data directly to Google Sheets from Twitter data scraper.


Can I also scrape tweets from the user with this data scraper?

No, this scraper only extracts user’s public profile data. It will only get you the number of tweets by a User. To scrape user tweets data, you can use the Twitter User Tweets Scraper.

No, this specific twitter scraper is not for trend monitoring. To monitor trends, scrape tweets and retweets on certain hashtags, you can use the Twitter Search Results Scraper.

How to scrape Twitter data using python?

You can use Twitter’s API with python libraries like Tweepy. For scraping data at scale, you can use Lobstr’s free API and create your own web scraping tool in python or javascript.

Can I scrape my Twitter followers using this data scraping tool?

This scraper only scrapes the number of followers of a Twitter user. It does not specifically visit a profile, gets your followers list, and scrapes their profiles.

If you need a scraper that can do that, or you have an idea for any other social media platform scraper, you can submit your idea here. We do have scrapers for LinkedIn and Facebook.


That’s a wrap on how to scrape Twitter profiles without coding. Check out our Twitter Profile Scraper – the fastest and most efficient Twitter scraper for free.

There are a lot of other web scraping tools in our store. Check them out. For more tutorials, do check out our blog.

Shehriar Awan - Content Writer at

Shehriar Awan

Self-proclaimed Head of Content @ I write all those awesome how-tos, listicles, and (they deserve) troll our competitors.