Planning to make #webspeed improvements? I'm sure you have a big list of them but are you really sure which would be the most effective? Turns out it's relatively easy to find out which of those technical changes will bring the biggest impact to #googlelighthouse / #googlepagespeed score with the lowest investments from your side (maximising the return on investment).
Daniel Heredia Mejias uses Python to work with Page Speed Insights API and Lighthouse Scoring Calculator so that you will be able to answer these questions and make decisions based on the best #ROI.
Lighthouse Scoring Calculator:
Twiddlers are used to manually re-rank any Google Search results of any search query for whatever reasons. This is internal guide for Google Search engineers showing how to use them in practice.
“We do not use human curation to collect or arrange the results on a page” Google constantly states. But many studies showed the exact opposite, and these twiddlers are a powerful tool to manipulate search results for political or whatever reasons. Elaboration stops here, you probably have already got the point.
View Google SuperRoot Twiddler Quick Start Guide at https://lnkd.in/dkmsabs
The document was leaked by one of the long-term Google employees. Please let me know if I'm wrong, but I recall it's the same guy who leaked the full and confidential version of Search Quality Rater Guidelines, and so Google "had to decide" to build and release public (censored) version of it later, now available at https://lnkd.in/dDja4PF.
Enjoying this Krisztian Balog's book on Entity-Oriented Search from the Information Retrieval Series (2018). If you'd like to learn how modern search works, this book is just the perfect starting point. It will introduce you to concepts, technologies and computer science fields vital for modern Web search (incl. Google), these include NLP (Natural Language Processing), Information Retrieval, Semantic Web ... and most importantly - entities.
And it is free. Get your copy at http://eos-book.org/
Subtopics are now live in Google Search.
Google has applied neural nets to understand subtopics around an interest, which helps deliver a greater diversity of content when you search for something broad. As an example, if you search for “home exercise equipment,” Google can now understand relevant subtopics, such as budget equipment, premium picks, or small space ideas, and show a wider range of content for you on the search results page.
We are also waiting for passage indexing update, guess it's coming shortly.
Google's post back from October (2020) about this and other features coming https://blog.google/products/search/search-on/