The Google Search - A New Media Interface
In the era of new media, there isn’t an interface to new media nearly so ubiquitous, well-known, or influential as the Google search. Since its advent in 1997, the Google search has become so ingrained in the daily lives of new media consumers that the verb “googling” was coined solely to describe the act searching the internet for information. In its most recent rendition (released August 8th, 2012), the simple, one text box interface allows users to type in a search query and access new media, such as web pages, images, and videos, that are related to the query. The search can be narrowed, expanded, filtered and manipulated. The interface even provides extras based on the query; it will give you attractions if you search for vacations in a certain area, it will display flight times if you search a flight number, and it will even correct your query if it thinks you entered it incorrectly. A more detailed description of how it works is available here. While not strictly a piece traditional piece of media (such as a book or a photo), this interface aligns almost perfectly with Lev Manovich’s principles defining new media in The Language of New Media.
Since the Google interface is a completely computer-based medium, it must have originated in numerical form. Manovich’s first, and most simple principle, is clearly fulfilled by the Google search. This numerical form, to which algorithms can be applied, takes advantage of Manovich’s second principle of new media - modularity. While the Google search has modularity in itself - searches yield pages, which consists of result blocks, each of which contains hyperlinks and other information - the beauty of the Google search lies in the modularity of the world wide web. Since the web has modular parts, a google search can parse web pages and extract items specific to the query. If you search for a picture, a Google search can parse out images from the rest of web pages, allowing a more targeted and quality search that divides the web into distinct, modular pieces. The individual access of all media elements on the web is essential, since we don’t have to grab the entirety of a site to search for one piece of media.
Knowing the Google search is in numerical form, is modular, and takes advantage of the modularization of the world wide web, the leap to Manovich’s third principle, automation, is an easy one. The Google search’s automation at the user level is easy to see: type in a query, Google accesses it’s database, and gives you the results. Underneath, however, the automation stretches to almost every aspect of the search. In order to make sites searchable, Google must find them on the internet and analyze them, attaching data such as where it’s located, the quality of the site, or how popular it is. In order to give search results, the Google search automatically parses these data tags, parses your query, and based on information gained from both sides, gives you the results. The actual process can be seen in the figure below. All of this has been automated, making the search and access of new media objects extremely easy.
These factors would be moot if the Google search didn’t also follow Manovich’s fourth principle, variability. Unlike non-digital methods of accessing, organizing, and aggregating old media, the Google bar is completely variable. Once a user enters a query, the page will change in order to display customized results. The page can change display based on the type of media results, how many results there are, what the query was, or even if it has similar information to display. Even the term “googling” is a result of variability; since a Google search allows for on demand access to customized search results, it’s variability made it key to quick new media access, leading to its ubiquitous implementation throughout the internet.
Clearing all of the first four principles laid out by Manovich, the Google search interface also satisfies his fifth, and probably most unique, principle of a new media object. The “cultural layer” of the Google interface (all of the new media content accessible via Google) is completely defined and framed in terms of the “computer layer.” Google is a transcoding non-digital methods of searching, storing, and accessing media. While the basic concept is the same - search for something, find it, use it - the methods in which this has been accomplished has been changed in order to work utilizing the fundamental structure and organization of a computer. Instead of having a collection of specific media (books, microfilm, newspapers, records, etc.), you can now generalize all media because it can all be handled by a computer. Items don’t have to be organized, but just placed in a database. Organization doesn’t occur via sorting, but rather tagging data to make it easier to search and handle. For instance, if a search result is tagged as local and matching the term, it will have higher priority than a result that isn’t local. If you search “Monet,” you will not only get textual information, you may get pictures of his work or even video relating to him. The figure below also shows how the Google search has helped to transcode traditional search methods into ones that can be run by the computer in under a second.
The Google search, a new media object as defined by Manovich, uses these principles to create the world’s largest portal of access to new media across the web. Congruence with all of these principles of new media laid out by Manovich not only make the Google search interface a new media object, but it also explains the large-scale use of it today.
Since the Google interface is a completely computer-based medium, it must have originated in numerical form. Manovich’s first, and most simple principle, is clearly fulfilled by the Google search. This numerical form, to which algorithms can be applied, takes advantage of Manovich’s second principle of new media - modularity. While the Google search has modularity in itself - searches yield pages, which consists of result blocks, each of which contains hyperlinks and other information - the beauty of the Google search lies in the modularity of the world wide web. Since the web has modular parts, a google search can parse web pages and extract items specific to the query. If you search for a picture, a Google search can parse out images from the rest of web pages, allowing a more targeted and quality search that divides the web into distinct, modular pieces. The individual access of all media elements on the web is essential, since we don’t have to grab the entirety of a site to search for one piece of media.
Knowing the Google search is in numerical form, is modular, and takes advantage of the modularization of the world wide web, the leap to Manovich’s third principle, automation, is an easy one. The Google search’s automation at the user level is easy to see: type in a query, Google accesses it’s database, and gives you the results. Underneath, however, the automation stretches to almost every aspect of the search. In order to make sites searchable, Google must find them on the internet and analyze them, attaching data such as where it’s located, the quality of the site, or how popular it is. In order to give search results, the Google search automatically parses these data tags, parses your query, and based on information gained from both sides, gives you the results. The actual process can be seen in the figure below. All of this has been automated, making the search and access of new media objects extremely easy.
These factors would be moot if the Google search didn’t also follow Manovich’s fourth principle, variability. Unlike non-digital methods of accessing, organizing, and aggregating old media, the Google bar is completely variable. Once a user enters a query, the page will change in order to display customized results. The page can change display based on the type of media results, how many results there are, what the query was, or even if it has similar information to display. Even the term “googling” is a result of variability; since a Google search allows for on demand access to customized search results, it’s variability made it key to quick new media access, leading to its ubiquitous implementation throughout the internet.
Clearing all of the first four principles laid out by Manovich, the Google search interface also satisfies his fifth, and probably most unique, principle of a new media object. The “cultural layer” of the Google interface (all of the new media content accessible via Google) is completely defined and framed in terms of the “computer layer.” Google is a transcoding non-digital methods of searching, storing, and accessing media. While the basic concept is the same - search for something, find it, use it - the methods in which this has been accomplished has been changed in order to work utilizing the fundamental structure and organization of a computer. Instead of having a collection of specific media (books, microfilm, newspapers, records, etc.), you can now generalize all media because it can all be handled by a computer. Items don’t have to be organized, but just placed in a database. Organization doesn’t occur via sorting, but rather tagging data to make it easier to search and handle. For instance, if a search result is tagged as local and matching the term, it will have higher priority than a result that isn’t local. If you search “Monet,” you will not only get textual information, you may get pictures of his work or even video relating to him. The figure below also shows how the Google search has helped to transcode traditional search methods into ones that can be run by the computer in under a second.
The Google search, a new media object as defined by Manovich, uses these principles to create the world’s largest portal of access to new media across the web. Congruence with all of these principles of new media laid out by Manovich not only make the Google search interface a new media object, but it also explains the large-scale use of it today.