May 16, 2013 by Baawraman
It is no secret that more often than not, we use Google as a verb- “ I Googled it”, “Google it and you’ll get the answer”, are some of common usages of Google as a Verb. Oxford dictionary, one of the most prestigious dictionaries of English Language, defines Google as:
Definition of google
search for information about (someone or something) on the Internet using the search engine Google
While Googling is a daily chore like criticizing the local government, bathing and brushing your teeth; introduction of Mobile technology seems to be a catalyst in these activities, according to a report, Android users Conduct 2.65 Mobile Searches per Day , which is more than the number of times an individual brushes his/her teeth in a day. Daily searches performed on Google are increasing with a rapid pace, and the reasons are quite obvious- School Projects, College Assignments, Local Dentists, Nearby Pet shops, Birthday Gifts/Ideas,How to’s, Movie Reviews, Recipes-you have the question, Google has the answer, If it isn’t on Google, it doesn’t exist.
Average Number Of Searches on Google Per Day(Year Wise)
Basic Methodology Of Google:
Initial method of ranking and collecting information was citation(links) bases which analyzed the information based on the quality and quantity of links by applying algorithms to provide best results for a given query, according to the initial research paper submitted at Stanford Uni entitled “The Anatomy Of Search Engine” :
The Google search engine has two important features that help it produce high precision results. First, it makes use of the link structure of the Web to calculate a quality ranking for each web page. This ranking is called PageRank and is described in detail in [Page 98]. Second, Google utilizes link to improve search results.
While there has been a number of changes and updates, Penguin Update for example, in order to better identify these links and thus provide better search experience. Citations and links are mostly created by publishers, not actual end user, a room for manipulating these links still exists. As per latest Algorithm updates from Google, the search quality has improved in recent years and we should expect regular updates from Google to further improve the overall quality.
After a series of regular updates , Google then made some significant changes in the basic methodology of search engine, Page rank , one of the major ranking factors, has lost its place in recent years and Social Signals came into the picture, because Social Signals is what a real end user can control and this is the reason why Google Launched Google Plus.
Yes, Facebook Is A Noun- Enter Graph Search
When I first read the news about Facebook Graph Search, and its tagline “Search People, Places and Things”, the first thought that came to mind was of my Primary English classes, where I was told and forcefully asked to accept the fact that “ A Noun Names Places, People Or A Things”.
So, we already had a Verb called “Google” in Searchsphere( Yeah, that’s not a proper English word) , and now its Facebook, a Noun.
Basic Methodology Of Facebook Graph Search:
As opposed to its most talked about competitor called “Google” or any other modern day search engine, Facebook Graph Search is not Crawling Based, FGS looks for the user intent while performing search and looks for semantically related accurate results by understanding the contextual meaning of search terms using Natural Language Processing. Although, Google has introduced services like Knowledge Graph, which is based on the same technology. Semantic search is a concept referring to technologies that make a search respond to what the user enters to try to better understand what the user wants to know. I am a huge fan of semantic search, reason being, a vast majority of searchers don’t actually know how to search, when Semantic Search is in place, it helps users to search for what they actually want to know.
Apart from this, Facebook Graph Search works on the fact that Facebook users are connected to each others and with things they like, places they’ve been to and various other ways of connections, the endpoints of these connections are called as “Nodes”. This has been explained in the Patent Application filed by Facebook called Search and retrieval of objects in a social networking system, click here to read more on the Patent.
The computer-implemented method of claim 9, wherein the social graph has nodes corresponding to objects and edges corresponding to relationships of the objects, the user being represented as one of the objects.
From the marketing point of view, if you want to get found in Facebook Graph Search results, you need to minimize this distance, i.e you need to make sure that you are in close connection with your potential customers.
A computer-implemented method comprising: receiving a query from a user; submitting the query to a remote social networking system; and receiving, from the social networking system, a combined result set comprising objects matching the query, the combined result set comprising objects obtained from a plurality of search algorithms performed by the social networking system; wherein at least a plurality of the objects of the combined result set are ordered based at least in part on measures of affinities of the user for the objects, an affinity of the user for an object comprising at least one from a group consisting of: a distance on a social graph between the user and the object, and a similarity between the user and the object.
The above explains two things:
Just like SEO, where fake links/ artificial link building is a real problem for Google, and people manipulating search engine rankings using fake links, Fake Likes in Facebook will be of no use, reason being the distance and affinities between nodes.
When user searches for “Dentist in Dublin”, the user is not looking for those web-pages where “Dentist, Dublin” appeared in the Title, Headings, anchor texts of the links pointing to the page, user wants dentists in Dublin with closest connections to his profile.
As explained above, semantic search will look for the nodes, connections and edges between the searcher and the search results. Facebook uses Unicorn Framework as the building block of its search, this framework helps in ranking and indexing of the search results. Facebook is extending the use of Unicorn to be a search engine, Unicorn is an inverted index framework and includes capabilities to build indices and retrieve data from the index. Sriram Sankar, Facebook Engineer, posted on the blog that “ Our goal is to maximize searcher happiness, which we do our best to quantify through metrics like click through rate (CTR), NDCG, engagement, etc. We have to measure the impact of ranking changes on all of these metrics to maintain a proper balance”.
Above is the Unicorn Framework to run ranking experiments where the happiness metrics are compared between various experiments against their controls, read the complete working of Unicorn Framework here on Facebook’s Notes.
I believe that Facebook and Google are too good to defeat each other, yes, they both can bring something really new, as in this case, Facebook came up with something which might looks like a competitor of Google, but in reality, its not. Google, on the other hand, recently applied for a patent entitled “Query based user groups in social networks”, Bill Slawski from Seo by the Sea covered this in his blog post :
Are Google’s query-based social circles the answer to Facebook’s Graph Search? Not too long ago, Facebook launched its Graph Search, which enables people to search for things like “My Friends who live in San Francisco,” and My Friends who like Surfing,’ and “Places my Friends like.”
Imagine if Google Plus allowed you to perform searches such as, “People who take the same bus as me into the city,” or “People who like to eat at the Red Truck Bakery,” or “People attending the Dave Matthews Band Concert next Friday,” and creates in response a social network circle that other people might be invited to join, even temporarily, or who could join anonymously. Or Google Plus may dynamically create such a query-based social circle which it may recommend that you share through as you create a post about a music festival you’re going to, or a meal you’re reviewing from a local hotel.
While there are few things on which Facebook needs to work in order to make Facebook Graph Search a better experience. With Graph Search Launch, I was expecting Facebook’s Open Graph Tags to mark their importance and internet marketing ninjas will include OGP tags in their technical checklist, I am not sure why Facebook didn’t emphasize on usage of OGP. Apart from this, when Likes and connections would be the key in Graph Search , SBM’s will find it very difficult, as Danny Sullivan said :
“Consider me. Not only have I not liked my electrician, my plumber, my dentist, my doctor or my tax person on Facebook, but I don’t even know if they have Facebook pages. I have nothing to offer to my Facebook friends in this regard.”
According to me, Facebook’s Graph Search will give us a new way to perform searches on internet, while Google will continue its dominance in traditional search market with new features in Google’s search technologies, Facebook will emerge as a new dimension in Search Market.
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