Social search has been a much talked about phrase in the internet marketing world for quite some time now. While it was supposed to pose a serious threat to traditional algorithm based search, social search has seen itself in a state of continuous evolution. It might take some more time for the challenge to be realized but still social search holds immense promise for improving our information gathering activities on the web. Let’s have a closer look at what social search is all about.
What is Social Search?
Wikipedia says, “Social search is a type of web search method that determines the relevance of search results by considering the interactions or contributions of users.” Just to make it simple, social search returns you personalized search results based on the user’s social network. This user-based approach is in sharp contrast to the traditional machine-based approach. Social search has many influencers, from simple shared bookmarks or tagging of content with descriptive labels to more complex ones that combine human intelligence with computer algorithms.
Looking Back
Social search as a concept is not really new. Right from the early days of the internet, even before the emergence of the first search engines, it has been in existence. Those were the days when people relied on pages with links to their favorite sites. One of the first such pages was created by the inventor of World Wide Web, Tim Berners Lee. And then Yahoo, one of the first directory web sites, was created by a team of human editors who surfed the web and wrote up brief descriptions of the sites they found. Some other classic examples are The Open Directory Project, the Librarians’ Index of the Internet which were created by people and have been around since the early days of the web.
Social Search Engines
Today people are flocking to social networking and book marking websites. These sites are the ideal launching pad for social search. There is a growing interest in how social groups can influence and potentially enhance the ability of algorithms to find meaningful data for end users and it’s no surprise that companies have sprouted with their focus on ranking search results according to one’s social graph on social networks. In 2008 start-ups like Mahalo, Wikia Search,Scour, Baynote, Delver and OneRiot have entered the social search space.
Social Search Pros
Social search engines have potential benefits deriving from the human input qualities of social search. Some of these include:
- Relatively free from link spam as there is less reliance on link structure of webpages
- More relevant search results as each result has been selected by users
- The user gets more current results
- The user gets his precise perspective reflected in the results
- The human judgment that social search uses is more accurate than computer’s ability to analyze a webpage
Social Search Cons
Despite the obvious benefits social search has some glaring defects too. As said earlier social search hinges heavily on human judgment. But the web today is growing at a pace which humans simply cannot match and this means there will be a lot of content that would remain unnoticed and hidden from the user. Also the tagging method through which the search works is not the ideal way of organizing web data. There is also the risk of spam because users have the freedom to directly add results to a social search engine which can be misused. We all know the way some SEO’s behave!
One final element that some people will have a problem with is the lack of privacy that social search includes. In order to learn about your own habits, search engines need to learn about your likes and dislikes and follow the websites you visit. My opinion? So be it. I seriously doubt Google, Yahoo! and MSN care about each individual enough for it to matter. The key is the collective research gained. It is much like the mistrust many had 10 years ago in purchasing products online. It isn’t really an issue now is it?
What’s Next?
Social search, the way it’s evolving integrates both automated software as well as human judgment regarding the nature of web content. In the future, it’s likely that a combination of algorithmic search and the various types of social search systems will work in tandem to satisfy a wide variety of information. And with support coming from giants and minnows alike in the webscape the future looks all rosy for social search. Remember – all search engines want to do is offer the user the most relevant search to their own personal preferences. Given this – social search and personalization are here to stay.
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9 Responses to “Social Search Like Never Before in 2009”
Han,
Good write up, your pro’s of social search are spot on. I do think its important to note the different types of Social Search. You mentioned some of the cons of social search and they are really only relevant when looking at the search engines like mahalo and other social search engines that allow explicit user feedback to drive search results.
You mentioned Baynote in the list of search engines, and I wanted to clarify that we do not drive our results with explicit user feedback like tagging or rating, and therefore Baynote Social Search is not susceptible to the types of gaming you mentioned. Our Social Search approach is fully automated and derives its social intelligence by watching observing how users interact with content on a given site. You can check out our technology page for a deeper insight on our approach. http://www.baynote.com/technology/input/
Warren Colbert
January 7th, 2009 at 1:31 pm
Yes, you’re right Hari. Nowadays social search is gathering great momentum over algo-based search. Google has also shown its leniency towards social search, as Marissa Mayer, Google’s leading VP in search, said social search hasn’t shown much promise, but if it does, Google would be in a good position to incorporate it in future.
January 7th, 2009 at 10:52 pm
@Warren:
Baynote was mentioned in the list of social search engines purely as an example. There was no intention to bracket it with any others or to ascribe any particular “gaming” methodology. Anyway thanks for the clarification and the link. It’s really helpful!
January 8th, 2009 at 5:59 am
Nice post, Google came with ‘personalized search’ in a way to defend social search. How come Ms.Mayer can said “search hasn’t shown much promise” it shows her ignorance in this field! hari you’re right – social search’s future looks rosy….
January 9th, 2009 at 12:13 am
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January 12th, 2009 at 2:06 pm
This is a good review of the pros and cons of social search as it exists today. I have only two comments:
1) In my experience, personalizing search based on the user’s personal social network is only one of many definitions of ’social search’ floating around these days. I believe it will be the more powerful version of ’social search’, but I see the term also used to describe people finder systems, social recommender systems, and human-written search entries (Mahalo). Each of those has a very different flavor from the others.
2) I also believe that the key to successful social search will be in its implementation, which will be tricky to execute. There are a number of considerations that we as researchers (me and others) and developers (the readers of this blog?) need to take into account: when and where will social search be most effective? which scenarios will make social search a natural ‘given’, and which ones should be spared? when is implicit vs. explicit social data better? Most importantly, in what specific ways do social inputs/metadata aid a search–only after failed search attempts, before embarking full blown exploratory queries, never for certain types of questions, etc?
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January 17th, 2009 at 6:28 pm
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