WordPress is arguably the most popular content management system out there today. The fact that 28.9% of all websites on the internet are powered by WordPress should give you a fair hint at its massive popularity and adoption. Although it’s primarily a blogging CMS, its versatility allows for building literally any kind of website you can imagine.
Anyone who’s tried to extract data from blogs can vouch that most of these blogs run on WordPress. This means, if you’re looking to scrape blog data, all you need to do is master WordPress scraping. While almost all WordPress blogs follow the same internal structure and elements, it still isn’t easy to write one crawler that can be guaranteed to work on all WordPress-based blogs.
Having taken up countless projects where our clients wanted to extract data from WordPress blogs, we already have a clear idea about the nuances of this niche and decided to create a dedicated solution to crawl WordPress blogs.
Our all new WordPress scraper is a dynamic solution that can scrape blog data from majority of blogs running on WordPress in an automated manner. It can understand the various data fields within a WordPress blog and automatically pull them, thanks to the powerful machine learning algorithm that powers the crawler.
Yes, we incorporated some serious machine learning capabilities into this WordPress scraper to achieve the level of accuracy and automation that it’s capable of.
With our years of expertise in the field of web crawling, we have enough sites at our disposal to train a machine learning algorithm that can mimic our engineers in the site setup aspect. While our engineers manually dig into the code to find the right fields and classes associated with them to set up the crawler for custom web crawling projects, here, the machine learning component effortlessly handles the field identification process for WordPress blogs.
Every data point displayed on a web page is tagged with a certain class name to address, call and style it on the page. A web scraper typically makes use of this class name to find subsequent records on a site after it has been manually told what class name represent what data point.
With our WordPress scraper, we basically cut down on this manual element, by enabling a machine learning algorithm to automatically identify the class names for various data points that we need to extract.
To facilitate this, the ML algorithm was fed with hundreds of thousands of examples that we aggregated from the web. Having reached a fair accuracy at detecting the data points by tagging fields, the scraper can now work on most WordPress blogs in a fully automated manner.
Here are some of the unique benefits of the solution:
As the machine itself handles the field matching process, the need for human intervention is literally nil here and this would mean faster access to data than ever before.
Unlike custom requirements where site changes would require manual intervention and code changes, the WordPress scraper can automatically update the crawler component in the event of site changes. This is taken care of by the Machine learning component as it scans the site every single time before initiating a complete crawl. Site changes, if any will be dealt by the algorithm as a fresh new WordPress site and a new crawler code will be generated for the same based on the newly identified tags.
In case you haven’t really considered scraping blog data yet, here are some of the popular applications of scraping blogs.
Media monitoring in itself has quite a lot of applications. Most brands crawl blogs relevant to their industry to find mentions of their brands and their competitors in order to capitalize on new opportunities or to take quick action to save their brand image in case of negative publicity. It is also a very good idea to index data from the influential blogs to spot current trends and anticipate future demand.
Media companies need quick and ready-access to the trending news and information out there on the web. This helps them be the first to report new stories, which is a deal breaker in this industry. Since most media sites run on WordPress, they can gather this data by scraping WordPress blogs.
Machine learning systems need massive amounts of data to achieve a good performance score. Blog data makes for a great source for many machine learning systems built for text processing such as Translation, Natural Language Processing, Sentiment Analysis and more.
‘Anything that can be automated should be automated’ is something that we strongly believe in. Our all new WordPress scraper powered by machine learning techniques is yet another step towards making web data extraction faster, seamless and easier for our customers. You can check out the WordPress scraping solution by going here.