Social Media and Search Engines
I am going to copy part of this blog post word-for-word because I think this has the potential to be very important over the next few years, if not already:
from Searchenginejournal
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What Social Media Can Bring to Search
The examples of Yahoo user reviewed restaurant searches or the ranking of videos in Google search are current uses of social media’s measurrestaurantsable variables of reviews, ratings, comments and/or video plays being a critical part of these searches, but social media goes far beyond restaurants and videos.
Monitoring social bookmarking services like Del.icio.us, StumbleUpon and Ma.gnolia can help search engines in multiple ways by:
* Indexing Sites Faster : Humans bookmark sites launched by their friends or colleagues before a search engine bot can find them.
* Deeper Indexing : Many pages bookmarked are deep into sites and sometimes not as easily linked to by others, found via bad or nonexistent site navigation or linked to from external pages.
* Defining Quality : If someone takes the time to bookmark a site, it usually has some quality to it.
* Measuring Quality : Essentially if more users bookmark a page, the more quality and relevance that site has. A site with multiple bookmarks across multiple bookmarking services by multiple users is much more of an authority than a site with only several bookmarks by the same user.
* External Meta Data : Users who bookmark sites tag them with keywords and descriptions which add an honest and unbiased definition which is created by the public and not the owner of the site.
* Co Citation : Social bookmarking sites tend to categorize sites and pages based upon the tags used by humans to describe the site; therefore search algortihms can classify these sites with their peers.
In addition, by indexing the social measurement variables such as commenting and votes at Digg, Reddit, Netscape and various niche oriented (all of those Pligg powered hubs), search engine algorithms can also benefit from social news sharing sites by:
* Number of Votes : Similar to the number of bookmarks, the more votes a page receives on Digg or Reddit, the more useful that information usually is. If the same page receives multiple votes across multiple social news voting sites, the higher quality the site.
* Categorization : Like Co Citation, categorization can help define the subject of a site, therefore better helping the engine address searcher intent.
* Commenting : The number of comments can be compared to the number of votes, the higher the comment to voting ratio, the more relevant the news story or site was to the user; therefore, more relevant to the searcher.
* Relevant Sites : Techmeme and Netscape (and hopefully soon Digg) suggest relevant pages and sites to the stories which make their ‘popular’ categorical pages via intra-linking or blog index monitoring. Engines can learn from these projects to help users find alternative or relevant selections in their search results.
To the best of my knowledge, no search engines are currently implementing all of these theories into their current algorithms, but we cannot overlook that Google has been a partner of Digg for years, Microsoft will soon be, Yahoo owns Del.icio.us and AOL runs Netscape. These social services also offer API’s and are completely open to search spidering, which makes these variables mentioned above available to search engines for the taking.
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