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TikTok is “cruising like a skyrocket in the USA and across the globe, making an innovative video experience that has leftward Facebook, YouTube etc. pushing to carry on.”
If we look at the USA users more than 18 years of age, the TikTok has touched 39.2 million unique visitors in April from 22.2 million in January, as per the Comscore data.
The platform has shown that it is much more than only a fantastic app as its algorithms have spread videos that can get real-world consequences. Let’s discuss some examples:
In a nutshell, TikTok, with its commanding algorithms, has a considerable real-world influence, particularly seeing that an average user spends nearly one hour daily watching videos using this platform! So, it’s essential to know what TikTok is showing to millions of people day-to-day, and for that, we need some real-time data.
Here, we have given a code to scrape TikTok data differently. The steps are given below:
An excellent point to start is gathering videos from provided users. We would utilize TikTok-API made by David Teather (use pip3 to install TikTokApi to find the package).
To gather videos from a Washington Post TikTok account, follow the code:
The object user_videos is now listing 100 video dictionaries (with one example dictionary given here). You would probably be interested in only some stats that you can scrape from the complete dictionary using the given function:
After that, we can drive from API-outputted user_videos listing to a good, clean table (i.e. Pandas data frame) using three lines:
Here is the result file (We have removed a few columns and rows to make that readable):
Here, you may be attracted in videos “loved” by the provided users. This is effortless to collect. Let’s observe which videos the authorized TikTok account had recently liked:
And the result file looks like to one from the last time, as it saves the listing of videos:
Suppose you wish to create a more extensive user listing where you can gather videos they post and like. You could utilize 50 most-followed TikTok accounts; though, 50 may not produce a sufficient sample.
An additional approach uses suggested users for snowball the list from single user. Primarily, we would do that for four various accounts:
tiktok is the app’s official account.
washingtonpost is among the preferred accounts
chunkysdead leads the self-proclaimed “cult” on this app
charlidamelio is the maximum followed account on TikTok
Thi is the code we have used:
And suggested users are given below:
Mainly, the listing of references for chunkysdead and washingtonpost was indistinguishable, and there are many overlaps between other recommendations; therefore, this approach might not provide you with what you want.
Another technique to make a more extensive listing of users is using getSuggestedUsersbyIDCrawler to keep the snowball rolling. To make the listing of 100 recommended accounts using TikTok like a seed account, you will need the given code:
It makes a listing that has various celebrity accounts, some of them are given below:
We have observed that the getSuggestedUsersbyIDCrawler technique starts to diversify and get smaller, additional niche accounts having tens of thousands of followers instead of hundreds of thousands or millions. It is good news in case you need a typical dataset.
If you need to collect an extensive data sample from TikTok, we suggest starting with recommended users’ crawler.
Finally, you might need to gather trending videos for easy content analysis or keep it up. The API makes it very easy, as follows:
And this is the result file for trending videos on 2 nd July 2020, Thursday afternoon:
That’s all for now! Thanks for reading! For more information about scraping TikTok video data using a TikTok video API, contact Actowiz Solutions directly! You can also ask for a free quote for mobile app scraping and web scraping services requirements!
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