Instagram Scraping: How to Do it? [A Complete Guide]

With over 95 million Instagram posts daily, this platform can be a valuable data source. However, it can be time-consuming to extract data on accounts manually. This is where web scraping can be helpful.

Instagram scraping is a type of automated data extraction process. It specifically deals with data from Instagram like posts, comments, likes, followers, etc.

As one of the most popular social media apps, Instagram data can help you gain valuable insights. The only thing you need to know is how to scrape such information.

This article will teach you how to get data from Instagram in two approaches. You’ll also learn how it works, where to use it, and other things to keep your project legal and safe.

 🔑  Key Takeaways

• As a popular sharing platform, Instagram has valuable data you can scrape for insights.
• Instagram scraping deals with data like user profiles, comments, followers, and hashtags.
• You can create an Instagram scraper tool for free using Python and some of its libraries.
• If you want code-free Instagram scraping, use paid Instagram scraper tools.
• Instagram data helps in market research, competitor analysis, content planning, and influencer marketing.
• Before scraping Instagram, follow the platform’s policies and copyright regulations.

Scraping Instagram Data: What It Is and How It Works

Instagram data scraping is simply taking information from Instagram accounts. With this process, you can gain valuable data for several purposes.

The data you can scrape on Instagram include the following:

1. Profiles

You can get all public information from Instagram profiles. This data includes posts, images, links, likes, and comments. You can also get a profile’s followers and who it follows.

2. Posts

You can get details about specific Instagram posts. For instance, you can get the post’s web address, link, date, likes, comments, and the username.

3. Hashtags

You can find and collect the web addresses of posts and media with a specific hashtag. 

There are different ways to scrape data from Instagram. You can use special tools or programming libraries that automate Instagram data collection.

There are two standard methods of scraping Instagram data:

1. Creating an Instagram Scraper with Python

Using Python to scrape Instagram can be complex. It requires technical knowledge but gives you more control over the data. 

2. Getting a Paid Instagram Scraper Tool

Special tools simplify the process, but some limitations exist on what it can scrape.

The following section explains these methods’ requirements and steps to scrape Instagram.

Requirements to Scrape Instagram Data (Python)

If you want to scrape Instagram data using Python, here are the things you’ll need:

1. Code Editor

A code editor is an app you need to create a Python script. Some popular code editors are Visual Studio Code and Sublime Text.

2. Python

Python is a programming language considered to be the best for web scraping. It has a library collection and tools suited to scrape Instagram data. This language also uses simple syntax, making it the best option for beginners.

To check if you have Python, open your Windows command prompt or macOS terminal and run this command:

Python -V

This command will return the installed Python version.

Besides Python, you’ll also need some of its libraries for this scraping task. These are:

1. BeautifulSoup

This Python module allows parsing and scraping HTML and XML pages. Thus, you’ll need it to parse the scraped Instagram data.

2. Requests

This Python module sends requests through Python. It usually works as an API tool, but you can also extract data from HTML.

3. Selenium

This Python module gathers all the necessary data with a WebDriver Browser Automation. With this tool, you can crawl your target Instagram URL and collect data at scale. 

4. WebDriver

This tool lets you control user agents. As a browser tool, it helps you manage the Instagram platform as you scrape data from it.

Steps to Scrape Instagram Data Using Python

Before you begin, note that scraping data using Python may require technical skills. Moreover, you must understand the rules of scraping.

Here is a simple guide for scraping Instagram data using Python:

Step 1: Open your code editor to write your Python code.

Step 2: Install the required libraries. You’ll need the BeautifulSoup, requests, and Selenium libraries to scrape Instagram.

To do so,  go to your computer’s command prompt for Windows or terminal for Mac and type these commands:

pip install bs4
pip install requests
pip install selenium

Step 3: Go to your code editor, create a new file, and save it with a .py extension. This example will use the file name: ‘scrapeinstagram.py’

Step 4: Import the required libraries in your Python script.

import requests
from bs4 import BeautifulSoup
from selenuim import webdriver
from selenuim.webdriver.common.keys import Keys
import time

Step 5: Go to your browser and download the suitable WebDriver. Then, put it in the same folder as your Python script. Now, set the web driver up in your script:

driver = webdriver.chrome(executable_path = ‘insert-the-web-driver-here’)

Step 6: Use the WebDriver to move to Instagram’s login page:

driver .get=(‘https://www.instagram.com/’)

username = ‘your-instagram-username’
password = ‘your-instagram-password’
username_input = driver.find_element_by_name(‘username’)
Password_input = driver.find_element_by_name(‘password’)
username_input .send_keys(username)
password_input.send_keys(password)
password_input.send_keys(Keys.ENTER)

Step 7: Use Selenium to search for the profiles or hashtags you want to scrape:

search_query = ‘insert-the-profile-you-want-to-scrape’
Search_queryf‘https://www.instagram.com/explore/tags{search_query}/’
driver.get(search_url)
time.sleep(2)

Step 8: Use Selenium to scroll through the page and extract the desired data. Then, add your scraping and extraction code to your script.

Step 9: Save your script, then open your computer command prompt or terminal. Move to the folder where you saved the script and run it using this command:

python ‘scrapeinstagram.py’

Once the script runs, you’ll see the extracted data on your scraping and extraction code.

That’s it! You have successfully scraped Instagram.

Steps to Scrape Instagram Using Scraping Tools

You can find tools and apps that can scrape Instagram data for you. 

With these tools, you can finish tasks faster without dealing with codes. Some examples of the best Instagram Scraper tools are the following:

• NimbleWay
• Bright Data
• ScrapingDog
• ScrapingBee
• PhantomBuster

Here is a simple guide to scraping Instagram with tools.

Step 1: Pick the data you want to scrape on Instagram, like posts, usernames, or hashtags.

Step 2: Select the right tool to scrape the desired data. Some of these tools do not support specific data.

Step 3: Provide the tool with the data you want to scrape. For example, if you are scraping a post, insert the URL of the post.

Step 4: Start scraping!

Step 5: Save the collected data in a helpful format like JSON or CSV.

Instagram Scraping Use Cases 

Instagram offers crucial data you can use for many purposes. Thus, many people try Instagram scraping to gain such data. Here are some of the use cases of this process:

1. Market Research

Instagram scraping gives marketers essential data points on their target demographics. These points are:

• Interest
• Location
• Buying patterns

With Instagram data, users can have a valuable basis for their market research. 

Market research will help identify customer behaviors. As a result, businesses can make fact-based decisions. 

2. Competitor Analysis

Instagram scraping can be helpful when you want to study your competitors. 

With data from your competitors’ accounts, you can find out their strategies.

Doing this can help you make better decisions on how to run your own business on Instagram.

3. Content Planning

Collecting data from your competitors shows you what is popular with your audience. Instagram scraping helps you see trending topics and what hashtags are popular.

Doing so helps you develop ideas for exciting and engaging posts. As a result, you can attract more followers and keep them interested in what you share.

4. Influencer Marketing

Instagram scraping helps you to find the right influencers for your brand. You can also find out how they engage with their followers, and you can follow suit.

Data scraping can help you discover influencers who match your brand well. And you can decide who to work with to promote your products or services.

Scraping Instagram Data: Is it Legal?

Scraping Instagram data is like borrowing information from a digital world. However, like in the real world, there are rules to ensure you’re on the right track.

Instagram has a strict policy against automated access to the platform without permission. When caught violating the Instagram scraping policy, you can issues like:

• Account Suspension
• IP Blocking
• Legal Action

Moreover, there are also laws about privacy and copyright that you must respect.

For example, you must know about Europe’s General Data Protection Regulation (GDPR). This regulation sets strict guidelines on how you should handle and protect data.

Conclusion

As one of the top social media platforms, Instagram holds crucial data you can use for many purposes. However, getting those data can be time-consuming. Thus, you need to automate this process with Instagram scraping.

You can do this process for free using Python and some of its libraries. On the other hand, you can use paid tools like NimbleWay and ScrapingBee.

Whatever approach you take, follow Instagram’s Terms of Service. You should also beware of scraping rules to avoid legal issues.

FAQs

By Muninder Adavelli

Muninder Adavelli is a core team member and Digital Growth Strategist at Techjury. With a strong background in marketing and a deep understanding of technology's role in digital marketing, he brings immense value to the TechJury team.