Knowing how to scrape youtube comments can help people undergo a brief analysis and make decisions based on the results. Collecting the data of video content, likes, and comments will help users with a collective understanding of what worked well and what did not. Data Reportal’s report on global audience reach says that YouTube has 2.476 billion users around the world in July 2022. This data clearly says YouTube is one of the most eligible platforms to conduct market research. This article will explain how to use such wide data from youtube to make business or financial decisions.
Whether you promote programs or provide information to students, Youtube is the best way to communicate to a wide audience. It is the second-largest search engine in the world, next to Google. As Google and other search engines tend to favor videos, you can improve your search engine ranking by sharing videos on Youtube with good titles, tags, and descriptions. You can also convey your brand messages on Youtube with the help of videos, as they are a perfect method to capture the emotion and the physical attributes of what you are promoting.
Youtube scraping allows you to scrape video data, subscriptions, comments, ranking, recommendations, and ads. With the help of the Youtube scraper, you can scrape your searches by picking data from the selected Youtube URL page. You can now scrape the channels, videos, and their details and the comments and subtitles, which opens a whole new dimension to analyze video data. You can scrape both auto-generated and added captions in various languages using web scraping.
Scraping data from Youtube is useful because of some of the following reasons.
You need to follow the below steps for scraping comments from Youtube using Python.
You have to import the necessary packages using the Python command as shown below.
!pip install datakund-bot-studio !pip install youtube-comment-scraper-python
Now, you need to import the required packages.
from youtube_comment_scraper_python import * import pandas as pd
You need to open your desired Youtube video link and go to the comments section using the below commands.
You will get the following output by executing this command.
After executing the above piece of code, you need to open your web browser where your video is already opened. It will automatically perform Page Down and scrape comments, so you need to wait for the process to finish. The time taken by this step can vary depending on the number of comments on a video.
data =  currentpagesource=youtube.get_page_source() lastpagesource='' while(True): if(lastpagesource==currentpagesource): break lastpagesource=currentpagesource response=youtube.video_comments() for c in response['body']: data.append(c) youtube.scroll() currentpagesource=youtube.get_page_source()
Now, we remove the duplicate data and convert our list to a dataframe. Then, we export our data to a CSV file.
df = pd.DataFrame(data) df = df.replace('\n',' ', regex=True) df = df[['Comment', 'Likes']].drop_duplicates(keep="first") df.to_csv('data.csv',index=False)
We check our data by using df.head() as shown below.
Youtube proxy is an intermediary server that provides data exchange between the device and the servers. It helps to create an indirect connection allowing you to bypass the firewall of your system administrator or Internet service provider. With the help of proxies, you can increase views on your Youtube videos and get more comments.
You need to open your command prompt and type the following.
$ git clone https://github.com/MShawon/YouTube-Viewer.git $ cd YouTube-Viewer $ pip install -r requirements.txt
Further, check your Google Chrome version and download the same version chromedriver.exe from https://chromedriver.chromium.org/downloads and place it in the chromedriver_win32 folder.
You need to filter the below command to filter good proxies if you’ve got a large proxy collection. Afterward, you have to use GoodProxy.txt for a proxy python file.
$ python proxy_check.py
The several possible reasons to use a Youtube proxy are as:
YouTube comments will help marketers or general users to understand the trend and opinions of the public. The frequency of brand mentions, likes, and dislikes will help users to measure their reach and make business decisions/financial decisions. Buyers can also use the data from the comments to decide whether to purchase a product or not.
To scrape youtube comments, we require two primary packages, they are youtube_comment_scraper_python and pandas. The former is responsible for performing scraping operations while the other allows data analysis operations.
Generally, proxies are blocked for certain places like schools, saying it is not necessary for students to get exposed to entertainment videos during school hours. To bypass this restriction proxy is required. Another important reason is scraping. A normal code or tool can not easily scrape a huge amount of data. To overcome this, we can use proxies with high bandwidth which can support scraping huge amounts of data.
Youtube is a great place for building an individual platform, and it is a place where you can do a ton of customer and digital marketing research. The comments section of Youtube videos gives a lot of insights about the expectations of people and what they like/dislike. You can scrape Youtube comments using Python, and you should use proxies when scraping them. It is because proxies protect you from getting blocked, and they also allow you to do more targeted research. You can use dedicated proxies for scraping Youtube. Though they are expensive, they are more secure than the other proxies.
Hope you got an insight into how to scrape Youtube comments using Python.