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  • Chapter 13 – Build an Instagram Profile Scraper to Scrape Instagram Email, Followers, Posts, and More
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Chapter 13 – Build an Instagram Profile Scraper to Scrape Instagram Email, Followers, Posts, and More

May 4, 2024

Search keyword volume tells us the trend of up and down implying the customer end demand momentum. It reflects the information, content and products that are demandable as well. Instagram is one of the most ideal places to understand how the business creates content and engages with audiences. It’s not surprising that most people are looking for a more efficient way to fetch the data and learn insights. You can use Python, or a software, or even manually collect. The answer is obvious. It’s because good value for money and time is the evergreen strategy.

In the previous chapter, I walked you through how to scrape potential Instagram partners by using hashtags and selenium. Basically, you are able to collect a list of hundreds of candidates by just spending 10 mins. Of course, this will not be the ending. It’s because learning trending content, monitoring your competitor’s latest activities, and automating communication must be the next step.

So in this chapter for digital marketers, I would walk you through two methods to collect Instagram user profile data. One is to continue using selenium arguments and syntax. The other is to use Beautifulsoup and JSON, apart from Selenium. By the end of this article, you can learn the logic to write the script, and of course, collect all the information in a single excel sheet.

Table of Contents: Build an Instagram Profile Scraper to Scrape Instagram Email, Followers, Posts, and More

  • Open and Read the Fetched Links in a CSV File
  • Method of Selenium find_element_by_xpath argument
  • Use Selenium, BeautifulSoup, and JSON method
  • Full Python Script of Instagram Email Scraper
  • FAQ
  • INSTAGRAM Latest Trending API Endpoint Recommendation

Instagram Profile Scraper – Open and Read the Fetched Links in a CSV File

In the previous Python Tutorial, we saved all the fetched Instagram hashtag’s post links, post likes, and the user’s IG profile link. So you can reuse the CSV file, and generate all the Instagram user profile links you are going to scrape.

Here are the codes to read the links. csv_reading [1] means the second column in the sheet is your scraping objective. It’s because 0 represents the first and 1 represents the second in computer science.

with open('dafdsfere.csv','r') as csv_file:
csv_reading = csv.reader(csv_file)
print(csv_reading[1])

In the sublime text, it represents working if you can print csv_reading and see the result of this KOL profile list.

Being said that, I am not going to highlight how to use selenium to login into your Instagram account and scrape. If you are interested in it, please check out the previous article of Chapter 12.

Chapter 12 – Build an Instagram Bot and Use Hashtags to Scrape Top Instagram Posts and Instagram Users

Instagram Profile Scraper – Method of Selenium find_element_by_xpath Argument

Now it’s time to scrape the data we want. First thing, we need to create a loop and only click through the column. Then, you can use selenium syntax to open the links. Below are the codes

for line in csv_reading:
links = line[1]
try:
Page = driver.get(links)
except Exception as e:
Page = None
try:

Secondly, you can inspect the object and copy the XPath. It’s for the purpose to lock the position and fetch the objective data. It’s the same as our previous approach.

Take the posts and followers for example. Post-XPath and follower XPath are listed below

//*[@id="react-root"]/section/main/div/header/section/ul/li[1]/span/span
//*[@id="react-root"]/section/main/div/header/section/ul/li[2]/a/span

So we can use find_element_by_xpath to fetch the data and use the text syntax to get the numbers.

PostNumber = driver.find_element_by_xpath('//*[@id="react-root"]/section/main/div/header/section/ul/li[1]/span/span')

PostNumber2 = PostNumber.text

FollowerNumber = driver.find_element_by_xpath('//*[@id="react-root"]/section/main/div/header/section/ul/li[2]/a/span')

FollowerNumber2 = FollowerNumber.text

Last but not least, you need to append the data and generate a CSV file by using pandas. For more details, please check out the chapter 12 article.

Instagram Profile Scraper – Use Selenium, BeautifulSoup, and JSON method

The cons in the above section are you can’t find the email element. It’s because only the mobile version shows the email contact button. And not all of the users show the email address in their profile.

For easier fetching user data, you can refer to Instagram JSON. This approach is very similar to fetching the Shopify product data we discussed previously.

Adding ?__a=1 behind Instagram’s user profile URL can show you the JSON data structure. I take this IG user for example. Basically, you can find what elements are open to access via API JSON. For example, they are emails, posts, followers, photos, external URLs, etc.

https://www.instagram.com/sophieapps/?__a=1&__d=dis

Regarding the Python script, the lines of coding are very similar to fetching by using the selenium find by XPath method. It’s different after defining the looping section.

Core lines of coding

First of all, you need to click through the URL links with additional parameters. So then, you need to convert the source code into an organized JSON format by using beautiful soup and JSON. Here are the codings

for line in csv_reading:
links = line[1]

page = driver.get(links + "?__a=1")

soup = BeautifulSoup(driver.page_source, "html.parser").get_text()

jsondata = json.loads(soup)

Then, it’s very similar to fetching Shopify product data. You need to find the path of each element of data you aim to fetch, and then create the codings. Below is an example to fetch the biography data.

biography = jsondata["graphql"]["user"]["biography"]

Last but not least, you can print a biography to see if it’s working. If it’s working, you can append the column data and save it as a CSV file. Here is a sample if you use the codings and generate the fetch data.

Full Python Script of Instagram Profile Scraper

If you would like to have the full version of the Python Script of Instagram Email Scraper, please subscribe to our newsletter by adding the message “Chapter 13”. We would send you the script asap to your mailbox.

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FAQ:

Q1: What is Instagram User Profile Data?

A: Instagram User Profile Data refers to the information and data associated with an individual’s Instagram profile. It includes details such as username, bio, profile picture, follower count, following count, and other relevant information.

Q2: How can Instagram User Profile Data be used for eCommerce?

A: Instagram User Profile Data can be used for eCommerce in various ways. It can be utilized to identify potential customers, analyze target audience demographics, understand user interests and preferences, and create personalized marketing campaigns to increase sales and engagement.

Q3: Is it legal to use Instagram User Profile Data for eCommerce purposes?

A: Using Instagram User Profile Data for eCommerce purposes is subject to Instagram’s terms and conditions, as well as applicable privacy laws. It is important to ensure compliance with these regulations and obtain proper consent from users before using their data for eCommerce activities.

Q4: How can Instagram User Profile Data be collected?

A: Instagram User Profile Data can be collected through various methods. These include using APIs provided by Instagram, scraping public profiles, utilizing data analytics tools, or partnering with third-party services that provide such data.

Q5: What are the benefits of using Instagram User Profile Data for eCommerce?

A: Using Instagram User Profile Data for eCommerce offers several benefits. It allows businesses to target their marketing efforts more effectively, personalize customer experiences, improve customer segmentation, and enhance overall sales and conversion rates.

Q6: Can Instagram User Profile Data help in influencer marketing?

A: Yes, Instagram User Profile Data plays a crucial role in influencer marketing. It helps businesses identify relevant influencers based on their followers, engagement rates, and niche. This data enables businesses to collaborate with the right influencers to promote their products or services.

Q7: Are there any limitations or restrictions in using Instagram User Profile Data?

A: Yes, there are certain limitations and restrictions in using Instagram User Profile Data. These include compliance with Instagram’s terms of service, privacy regulations, and restrictions on scraping or using private user data without proper consent.

Q8: How can businesses ensure the security and privacy of Instagram User Profile Data?

A: To ensure the security and privacy of Instagram User Profile Data, businesses should implement strong data protection measures, such as encryption, secure storage systems, access controls, and regular audits. It is also important to comply with relevant data protection laws and regulations.

Q9: Can Instagram User Profile Data be used for remarketing or retargeting purposes?

A: Yes, Instagram User Profile Data can be used for remarketing or retargeting purposes. By analyzing user profiles and behavior, businesses can target specific audience segments with personalized ads, promotions, or content, thereby increasing the chances of conversion and repeat purchases.

Q10: What are the ethical considerations when using Instagram User Profile Data for eCommerce?

A: When using Instagram User Profile Data for eCommerce, it is important to respect user privacy, obtain proper consent, and adhere to ethical standards. Businesses should be transparent about their data collection and usage practices, and provide users with clear opt-out options and control over their data.

Instagram API Endpoint Recommendation

Instagram Trending Post Scraper API

Price: US$18

Instagram trending post scraper crawl the most trending and popular post from Instagram.com. Users input a hashtag keyword and her/his account credntial to generate a list of specific posts. It returns the post URL, profile name, and post copy. API allows to fetch the Instagram profile data which includes profile followers, historical posts, post performance, etc

More API options from the Instagram collection. 

SAVE UP TO 50% and EXPLORE MORE!

Tags: Email Scraper, Global Social Bot Collection, instagram, Python for Digital Marketers

Continue Reading

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Next Chapter 4: Create a Website Bot to Scrape Specific Website Data Using BeautifulSoup

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