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Top 5 Twitter (X) Scrapers of 2024: Overview of Tools & Practices

Updated on Jun 24
8 min read
Written by
Gulbahar Karatas
Gulbahar Karatas
Gulbahar Karatas
Gülbahar is an AIMultiple industry analyst focused on web data collection, applications of web data and application security.

She is a frequent user of the products that she researches. For example, she is part of AIMultiple's web data benchmark team that has been annually measuring the performance of top 9 web data infrastructure providers.

She previously worked as a marketer in U.S. Commercial Service.

Gülbahar has a Bachelor's degree in Business Administration and Management.
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Twitter, has recently rebranded itself and is now officially known as “X”, is one of the most influential social media networks, with approximately 350 million active users as of 2023.1 Users send billions of tweets per day, contributing to a vast reservoir of data. This data serves as an important resource for businesses since it provides insights into public opinion and consumer behavior.

However, manually sifting through this significant amount of data is challenging. Twitter scrapers enable users to automate the process of collecting and organizing Twitter data. They allow businesses to transform the unstructured data on Twitter into structured and usable data. The collected data can be used for various purposes, including social media monitoring, lead generation, data mining, collecting data for LLMs and training LLMs.

In this article, we explain what Twitter scrapers are, how they work, and the challenges they face. We will also explore best practices for using these tools effectively while adhering to Twitter’s policies and ethical data scraping practices.

Top Twitter (X) scrapers of 2024: Quick comparison

The table below shows the total number of B2B reviews collected from reputable B2B review pages (Trustradius, Gartner & G2) as well as the average ratings they receive from users.

VendorsPricing/moFree trialPAYG
Bright Data$5007-day
Smartproxy$501 month
NetNutCustom offering7-day

The list is sorted in descending order for number of B2B reviews with the exception of the sponsors of this article which are featured with links.

While deciding the leading Twitter scrapers in the market, we have taken into account: 

  • Number of B2B reviews: 10+ reviews on review sites such as G2, Trustradius, and Capterra.
  • Number of employees on LinkedIn: 15+ employees on LinkedIn.

What is a Twitter scraper?

A Twitter scraper is software that is used to extract data from Twitter. Twitter scrapers enable users to collect various types of data associated with Twitter content, such as user profiles, hashtags, and tweets.

Best Twitter scrapers for scraping Twitter data

1. Bright Data

Bright Data is a data collection platform that provides tools and services for web scraping, including proxy servers, APIs, and no-code solutions. Bright Data’s Web Scraper IDE enables individuals and businesses to scrape data from public Twitter profiles, including images, videos and hashtags.


  • Suitable for beginners: Bright Data’s Twitter scraper allows users without coding skills to extract data from the platform.
  • Handle dynamic content: Dynamic websites change their content on the client side, making it harder to scrape the content for a web scraper. Bright Data’s web scraping tool handles dynamic content challenges automatically. 
  • Emulate a user in any geo-location: The scraper makes your Twitter scraper appear as it accesses the website from a desired location. 
  • Auto-scaling infrastructure: Automatically adjusts the amount of resources that your web scraper uses.  
  • Built-in debug tools: Provides built-in debugging tools for developers. It debugs issues in a past crawl to help users watch your scripts as they run. 
  • Auto-retry mechanism: When the connection request encounters a failure, the scraper waits for a predetermined time and sends the request again. 


2. Smartproxy

Smartproxy offers an API for social media scraping, including platforms Twitter, Instagram and TikTok. The scraping API allows users to scrape Twitter data points in JSON format, such as profiles, usernames and search results. 


  • Synchronous or asynchronous requests: Enables users to send synchronous and asynchronous requests to the target website. For example in a synchronous request method, you need to wait for the response before making the next request. This can make the scraping process slower, if you intend to collect a large amount of data. 
  • Anti-bot protection: Integrates browser fingerprints into your web scraping API, mimicking a real user’s browser fingerprint to make your requests appear more like legitimate user traffic.
  • Proxy integration: Provides 50M+ proxies, including residential, datacenter and mobile proxy IPs.
  • Anti-bot protection: Integrates browser fingerprint to overcome bot-detection measures. 


3. Nimble

Nimble is a web data platform specialized in data collection, offering a range of scraping APIs designed for different needs like Search Engine Results Pages (SERP), E-commerce, Maps, and a general Web scraping API. These APIs are enhanced with built-in residential proxies, including both static and rotating options, which are ideal for gathering data from social media. Additionally, the Web API provides specific features such as page interaction capabilities and parsing templates.


  • Delivered in: Nimble Web Scraping API provides three methods for delivering data:
    • Real-time: Data is collected and immediately returned to the user.
    • Cloud: Collected data is moved to a cloud storage selected by the user.
    • Push/Pull: Data is stored on Nimble’s servers, and users can retrieve it via a provided URL for download.
  • Batch processing: Extracts data from up to 1,000 URLs in one batch operation.
  • Automated parsing: Identifies the structure of the data and extracts the relevant pieces of information like product names and prices from e-commerce sites.
  • Residential proxies: Each query made through Nimble APIs is handled through a residential proxy.


  • Starting price: $600/mo
  • Trial: Available

4. NetNut

NetNut stands out as a reliable figure in the proxy market, offering both residential and datacenter proxies tailored for web scraping applications. They offer a social media scraping API that allows for the extraction of both live and on-demand data from sites such as LinkedIn. This social scraping solution supports proxy use and includes automatic proxy rotation to enhance the efficiency of data gathering.


  • Real-time and scheduled data extraction capabilities: Facilitates both immediate and planned data scraping tasks.
  • Automated proxy rotation: Automatically changes IP addresses for each session by default.


5. PhantomBuster

PhantomBuster offers Twitter Follower Scraper that allows users to extract the follower information from a public Twitter profile.


  • Scrape data by a URL input: The scraper allows users to scrape public follower information by a URL input. You can scrape the URL of a single user account or the URL of a Google Sheet containing a list of Twitter account URLs. However, you cannot collect data using a keyword or hashtag as the input.
  • Choose the number of profiles: You can select the number of followers you want to scrape.
  • Watcher mode: Reprocess the same Twitter profile URL during each launch to search for new followers.
  • CSV format: Export the collected data to a CSV file.


  • Starting from: $59/mo
  • Free trial: 14-day free trial

Most social media platforms, like Twitter, generally do not favor being scraped, as it can lead to increased traffic on their platform. That’s why, they implement different anti-scraping measures, such as rate limits, to prevent automated web scrapers.

Twitter proxies help users maintain anonymity and avoid restrictions or limitations such as IP-based blocking, rate-limiting, or geo-restrictions. When using a proxy server, it is crucial to adhere to Twitter’s Terms of Service and API usage policies.

Smartproxy offers a pool of diverse IP addresses to help users access geo-restricted Twitter content and bypass IP-based restrictions by rotating their actual IP address.

6. Apify

Apify’s Twitter scraper extract publicly available Twitter information, including hashtags, threads, replies, images and historical data. You can download the extracted data in any format.


  • API access: Enables users to access and control their Twitter scraping tasks using RESTful API.
  • Scheduler: Users can schedule their web scraping tasks at specific times or intervals.
  • Scrape tweets by search term or URL: Offers users to scrape Twitter data either by a search term or URL input.
  • Set a specific date: You can scrape tweets within a specific data range.
  • Proxy configuration: You can choose which proxies to use, including custom proxies and automatic proxies. You can either pick your proxy servers or use the automatic proxy offered by the scraping tool.


  • Starting from: $49/ mo
  • Free trial: Available (data retention for 7 days)

7. Octoparse

Octoparse is a web scraping platform that provides different web scraping and automation solutions for extracting data from web sources. They offer a data collection solution for extracting social media data from social media platforms, including Twitter, Instagram and TikTok.


  • Cloud data extraction: Performs Twitter scraping on the cloud, save the scraped Twitter data on the cloud rather than user local machine.
  • Automatic IP Rotation: Have built-in IP rotation feature, improving the success rate and reliability of Twitter scraping tasks.
  • Handling dynamic pages: Interact with the dynamic elements on the target profile page by clicking buttons, scrolling down the page, and filling out forms.
  • Auto-detection: Allow web scrapers to identify and select the desired data without requiring manual selection of data elements.


  • Starting from: $89/mo
  • Free trial: 14-day

Which Twitter data can you scrape?

It is essential to respect Twitter’s Terms of Service and follow their guidelines when collecting their data. That being said, you may be able to extract the following types of data:

  • Twitter profiles: Profile description, image, username, and follower/following counts.
  • Tweets: Metadata associated with the content of a tweet, including likes, retweets, and replies. 
  • Hashtags: You can collect tweets containing specific hashtags.
  • Twitter lists: List names, descriptions, and memberships.

The legality of scraping Twitter data depends on several factors, including the jurisdiction you are in, how you extract the data, and how you use the retrieved data. If you intend to scrape Twitter data, it is recommended to consult with a legal expert in your area to understand the legal implications before conducting any social media scraping activities.

What are the best ways to scrape Twitter?

There are typically two ways to access and obtain Twitter data: web scrapers and web scraping APIs. The choice between these methods depends on your specific needs and circumstances.

Factors such as the level of programming expertise and the size and complexity of your scraping project can influence the decision-making process in selecting the most appropriate web scraping method. Regardless of the web scraping technique used, it is crucial to use these techniques responsibly and comply with Twitter’s Terms of Service.

1. No-code Twitter scrapers

No-code Twitter scrapers allow users to collect publicly accessible data from Twitter without writing any code. They make it easy for non-programmers to collect data from the platform.

Advantages of no-code Twitter data scrapers:

  1. Handling dynamic content: Twitter’s dynamic content makes it difficult for web scrapers to effectively scrape data. Some no-code Twitter scrapers handle JavaScript, AJAX and other dynamic elements on web pages.
  2. Visual data selection: Web scrapers with visual data selection capabilities enable users to select the data elements they want to gather through a point-and-click interface (Figure 1). Visual data selection eliminates the need for writing code or defining selectors manually.

Figure 1: Showing how visual data selection works

Source: Octoparse

  1. Anti-scraping protection: Most of the no-code Twitter scraping tools offer anti-scraping protection technologies such as CAPTCHA solving services and IP rotation.

Disadvantages of no-code Twitter data scrapers:

  1. Limited customization: No-code Twitter scraping tools may be less flexible than custom code-based solutions.

2. Python Twitter scraper

You can build your Twitter scraper using Python library to simplify the process of accessing and using the Twitter API. Tweepy is a Python library for interacting with the Twitter API.2 It allows developers to handle the complexities of API authentication and data parsing. Here’s a simple tutorial on how to use Tweepy (Python) to access Twitter data:

  1. Register for a Twitter Developer account.
  2. Install Tweepy using pip:

3. Write a Python script to access and extract data from Twitter using Tweepy library. However, Twitter API rate limits may make it difficult for developers who intend to obtain massive amounts of data. The rate limits differ depending on the API type (Standard, Premium, or Enterprise) and API endpoints accessed. The most frequently encountered request limit interval is 15 minutes.3 For example, rate limits for the Standard API are divided into 15-minute intervals.

How to scrape Twitter data: a step-by-step guide

Here is a general breakdown of how a Twitter scraper works:

  1. Enter the target URL: Input the URL of the Twitter search result page you intend to scrape. You can collect data using URLs or search queries such as keywords and hashtags.
  2. Load entire content: Since Twitter is based on Javascript, you need to wait until the whole page loads before scraping.
  3. Select data elements you want to scrape: Locate the items to be extracted, such as the tweet content, username, and timestamp.
  4. Configure show more buttons: Since tweets are no longer limited to 280 characters, you may encounter a “show more” barrier when scraping the content of tweets. You will need to identify the “show more” element to scrape the expanded tweet content. Ensure that the Twitter scraper you select is capable of handling pagination, infinite scrolling, and other dynamic web elements.
Source: CNET4
  1. Run the scraper: Some Twitter scraping tools allow you to run the scraper at specific times or intervals on your local machine or in the cloud.
  2. Export the scraped data: Export the data to various formats such as CSV, Excel or JSON.

More on social media scrapers & proxies

Social media scraping

Social media proxies

Check out our data-driven list of web scrapers for help choosing the right tool, and get in touch with us:

Find the Right Vendors
Gulbahar Karatas
Gülbahar is an AIMultiple industry analyst focused on web data collection, applications of web data and application security. She is a frequent user of the products that she researches. For example, she is part of AIMultiple's web data benchmark team that has been annually measuring the performance of top 9 web data infrastructure providers. She previously worked as a marketer in U.S. Commercial Service. Gülbahar has a Bachelor's degree in Business Administration and Management.

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