Skip to main content

How To Extract Email Address Data From YouTube?

 how-to-extract-email-address-data-from-you-tube-jpg

Many people are looking for newsletter subscribers as well as there are many ways of doing that. In this blog, we will share with you a well-organized method, which helps you search for right targets.

Let’s take this look step-by-step. Visualize you’re a programmer as well as you’re concerned about developing web apps using Laravel Framework as well as you wish to share that with the people or selling that or whatever you need.

Therefore, you need to search YouTube for an associated video. For instance:

So, now we need to extract all comments from this video but HOW?

Google has given an API, which we can utilize to do work like this. That code snippet could help us do whatever we wish:

$.ajax({
        dataType: "jsonp",
        type: 'GET',
url: "https://www.googleapis.com/youtube/v3/commentThreads?key=PUT-YOUR-KEYXXXXXXX&textFormat=plainText&part=snippet&videoId=PUT-YOUR-VIDEO-ID",
        success: function(result){
            data = result;
            $('.data').text(data);
            console.log(data);
    }});

You will have your keys from here.

After scraping data, you’ll go for a technique to choose only email Ids from a string content. Many open source codes are there and you can utilize them or you can write your personal => example

For non-programmers:

You can utilize YouTube Comment Scraper from Web Screen Scraping as it’s easily usable. Just enter links of the videos and click Extract. You could download comments in different formats like JSON and CSV.

Let’s a try it on the example given above:

lets-a-try-it-on-the-example-given-above

You can download a JSON file as well as copy and paste a JSON file in this YouTube Email Address Extractor or Email Service Scraper to choose email addresses only.

to-choose-email-addresses-only

If you have any queries or want to know more about our YouTube Email ID Scraper then contact Web Screen Scraping or ask for a free quote!

Comments

Popular posts from this blog

What Are The Top 10 Advantages Of Amazon Data Scraping?

  Amazon is identified as the world’s biggest Internet retailer as far as total sales, as well as market capitalization, is concerned. This e-commerce platform consists of a huge amount of data, which is important to online businesses. Here in this blog, we will discuss the top 10 reasons why people scrape data from Amazon. Online shoppers are progressively becoming more self-confident in buying their smartphones or laptops online. Today, many shoppers do their online searching on Amazon and avoid search engines like Yahoo or Google altogether. The trustworthy base of Prime members is invaluable for Amazon because they are key to the huge success of this retailer. Although to convert typical online consumers to customers, e-commerce merchants need to use data analytics for optimizing their offerings. Why Do You Require Amazon Scraping? Being a retailer, it’s easy to think about how important data and information Amazon carries: reviews, ratings, products, special deals, news, etc. ...

Why Entrepreneurs Should Use E-Commerce Scrapers?

  For retail shops, the competition has become limited as it comprises other shops near your location. However, online e-commerce stores have similar online stores across the world. So, it’s almost impossible to keep an eye on competitors online amongst thousands worldwide. For retail shops, the competition gets limited as it comprises other shops near your place. However, online stores have very much similar online shops in the world in terms of competition. Relevant news, updates, and information associated to customer preferences help an organization of working accordingly. These information scraps could drive e-commerce ventures to wonderful heights. In that regard, data scraping is important for your business. Using data from an online field is a skill, which can assist e-commerce entrepreneurs in striking gold! Why Web Scraping is Important for E-Commerce Websites? Web data scraping has arose as a vital approach for e-commerce businesses, particularly in providing rich data i...

How to Scrape Glassdoor Job Data using Python & LXML?

  This Blog is related to scraping data of job listing based on location & specific job names. You can extract the job ratings, estimated salary, or go a bit more and extract the jobs established on the number of miles from a specific city. With extraction Glassdoor job, you can discover job lists over an assured time, and identify job placements that are removed &listed to inquire about the job that is in trend. In this blog, we will extract Glassdoor.com, one of the quickest expanding job hiring sites. The extractor will scrape the information of fields for a specific job title in a given location. Below is the listing of Data Fields that we scrape from Glassdoor: Name of Jobs Company Name State (Province) City Salary URL of Jobs Expected Salary Client’s Ratings Company Revenue Company Website Founded Years Industry Company Locations Date of Posted Scraping Logics First, you need to develop the URL to find outcomes from Glassdoor. Meanwhile, we will be scraping lists by j...