What do you need when you want to provide data scraping on LinkedIn? To cope with the web scraping LinkedIn task, you need a toolset. These toolsets have overall name scrapers, and you can use several types of scraping tools for LinkedIn. Here is a brief explanation of each of them.
The best scraper for LinkedIn: what are the options?
Scraping websites and their Pros&Cons
The first and most obvious way how to scrape LinkedIn is to use online scrapers built into the site structure. Such services are widely represented on the market today, and everyone can use them. But there are also some peculiarities. For example, the inability to process large data arrays with such built-in scrapers. Or the need for an expensive subscription if you need a LinkedIn web scraper all the time.
Hand-written LinkedIn scraping tools
Another option for data scraper for LinkedIn is small applications written by developers for each specific task. Such algorithms are quite suitable if you need to select only one or two parameters, but for large-scale parsing and subsequent processing of data into a convenient and readable form, they will not be enough. In addition, to create such LinkedIn data scrapers, you will either need to have enough programming skills or hire an experienced developer.
Web scraper for LinkedIn: API-based solutions
Today it is obvious that effective LinkedIn web scraping requires agile solutions. The API-based LinkedIn scraping tool is the solution of that kind that is obviously the best LinkedIn scraper tool.
As LinkedIn itself uses OAuth-based API for its users' profiles, there is a good opportunity to do the same with Python LinkedIn scraping API.
As for the merits you can get when using LinkedIn API data mining they are as follows:
You can use both paid and free versions of such LinkedIn scraper tools.
The efficiency of API solutions is higher than that of algorithms or web scrapers.
Fine-tuning most of the best LinkedIn scraping tools allows you to parse and extract only the data you need.
Want to try LinkedIn API scraping? You can get a complete picture of all the possibilities of such solutions using Data365.co
as an example.