Google does make some effort to identify content from other networks. But some SPYW features only highlight Google+ material, even when other services are more relevant. If Google favors its own product over a better result, users get the short end of the stick. Some engineers from Facebook, Twitter and Myspace have built a browser extension called Focus on the User to prove the point. But what about Google+ users? For them, Google+ results are the better result. Arguably, Google should cater to them, as users of its service.

Google's Choice: Help Google+ Users Or Help Others

When a large-scale Web service puts an opt-out switch on a new feature, it's because its designers believe users will like the feature. If the Google+ comments on our stories are any indication, Google+ users like this personalized search just fine.

But Google and its fans have two other use cases to consider. People who would rather have their personal website, Twitter or Facebook profile appear above Google+ are not well-served by Google anymore, nor are people whose social graphs exist on networks other than Google+.

Google has no obligation to these users. It can arrange its services however it wants. They're free, after all, as the underpinnings of Google's ad business. But Google itself has enough information to determine when a Facebook profile would be more relevant than a Google+ profile in its "People and Pages" box. It can tell when a Facebook profile has more subscribers and activity than a Google+ page.

The "People and Pages" box has hard-coded instructions to display Google+ instead. That might make Google less useful to people who don't use Google+, but it's more useful for those who do.

Focus On The User, Not The Service

The people who built Focus on the User used Google's own search signals to route around the Google+ integration when other results are more relevant. Larry Page returns a Google+ result, but Mark Zuckerberg returns a Facebook result. Danny Sullivan at Search Engine Land extensively tested the Focus on the User plug-in, and it worked like a charm; the profiles with the most activity and information came up first, whether they're from Google+ or not.

John Battelle has had some interesting chats with Facebook's Director of Product, Blake Ross, one of the developers of Focus on the User. The tool has gone through several phases, the first of which was just to remove all references to Google+. The tool released today is more thoughtful than that, as Battelle points out. It produces the most relevant result as measured by links, references from many other networks, and overall activity. You can read the code right on the website to see how it works.

Google+ Users Want Google+ Results

According to the Focus on the User developers, Google search should provide the most relevant result without assuming anything about the user's preferred social network. That way, the result that best represents the person or topic being searched for will be at the top. By this definition, "Search, plus Your World" should represent the world most accurately.

But does that focus on the Google+ user? For those who want Google+ to be their social network, the best result for their "world" might be the Google+ page, even if the owner barely uses it or just re-posts things from Facebook or Twitter. The Google+ user wants Google+ results. Shouldn't Google focus on the user of its own service?

The best solution to social search would be one that lets the search user decide what network(s) to prefer. To the extent that a social search engine doesn't prefer the user's own networks, it's not social search; it's just search. Maybe those results are more relevant, and maybe social search creates a filter bubble. But for those who want Google+ to be their "world," Google's social search works.

If Google+ social search is not for you, try Focus on the User and let us know how it goes.

Do you want personalized search results? How would social search work best for you? Sound off in the comments.

It's hard to learn to use Twitter, and users give up easily if they don't get it. Summify can help Twitter show new users why they should use the service. Twitter's latest changes are all about discovery of new people and content. Summify isolates the most meaningful stuff in one's Twitter feed, which helps users get value out of it.

Starting today, Summify has disabled new account registrations and some features. Summaries can no longer be public and profile pages and influence pages are gone. Summify used to auto-tweet for a user after generating a summary, mentioning the people whose links were featured, but this feature is now disabled.

Existing users of Summify will still get their private summaries via email and the iPhone app, but "at some point," the team says, "we will shut down the current Summify product."

Summify picks out key stories from a Twitter stream by scanning the user's contacts and social networks. It looks at shares of a story on Twitter, Facebook and Google Reader, and it considers the story's popularity within the user's own network as well as globally. The constant stream of Twitter updates can be too much to digest, so Summify built a way to automatically discover the most interesting stuff.

Discovery is Twitter's key problem to solve. If it wants users to stick around, it needs to help them learn to find the things that interest them. That's what Summify's core technology does.

A Moment of Op-Ed

I've got to say "good riddance" to Summify's auto-tweeting. This might have been a nice feature for some, but for people who write lots of blog posts, I found it really annoying. If you tweeted a lot of links to enough people, even if they weren't your links, you were bound to end up in a few of these a day.

I had to scour the Summify website to find out how to stop it. The only way to opt out of being mentioned was to manually ask the team, and I had to do it a bunch of times before it worked.

Twitter users should think carefully about services they allow to tweet for them, especially when they mention others. When an automated service mentions someone all the time with the same stock tweet, it is bound to annoy them. I'm glad Summify is done doing this. Now I'm looking at you, Paper.li.

If you search for a topic or hashtag, such as "SOPA," a post box at the top promps the user to "join the discussion." Posts from this box include the note "Shared from the Google+ SOPA stream." The topic name links back to the search results page.

Earlier this month, Google unveiled its pivotal effort to make search more social. Its "Search, plus Your World" update changes its search engine from an unbiased look at indexed pages to something influenced by your friends and contacts. Google's bet is that this helps users find more relevant results.

Google's real-time, topic-tagged social searches now give it a graph of the online public's interests, which is the same valuable commodity on which Twitter is trying to build its business. Twitter's torrent of real-time data produces trends, and it sells promoted ad spots on those trends. For users, search is an essential part of exploring their interests on these networks, so it's a crucial spot for these networks to monetize, too.

Twitter has been slow to build its own search product. For a while, Twitter just fed its results to Google. But that put too much power in Google's hands, and now Twitter won't play ball. Twitter acquired its own social search startup last September, but nothing has come of it yet.

Much like Twitter's website, Google+ search pages show trending topics along the right side, employing its real-time search and hashtags to discover new, timely content. Today's update makes Google+ searches more visible by including them in sharing. Google+ also added its "What's Hot" section to the mobile Web version today, adding another way to discover real-time Google+ stories.

Do you use search or browse for topics on social networks to find stuff that interests you? Or do you discover content in other ways? Tell us in the comments.

Search has a toggle switch now. One side recommends things based on your friends and connections, the other is a plain old search engine. Many bloggers still feel that it's terrible, whether you can turn it off or not. Others find it useful, if you're good about managing your contacts. One objection to the change is that it privileges Google content over objectively better results. Others find evidence that Google's definition of "Your World" is bigger than Google+. What about you? Are you mad enough to dump Google?

It wasn't clear before that Google would give users the option to turn off Google+ integration into search. Fortunately, it did, either temporarily or permanently. Some feel that opt-out isn't good enough, since most people can't be bothered or don't understand. Danny Sullivan has highlighted lots of evidence that Search Plus Your World is really all about Google's world, even for signed-out users, so maybe the opt-out doesn't even help.

Is it that bad, though? Our Marshall Kirkpatrick points to a bunch of great use cases in which Search+ is quite helpful, provided you've managed your Google contacts well. But it's clear that there are cases in which Google will point to itself ahead of a better result. Google will say that's just the way it is in the early days, and the feature will get better in time. But for people who demand a more objective search engine, enough is enough.

So what will you do? Do you have Search Plus Your World yet? Did you opt out right away? Has it helped you, or is it annoying? For those who can't stand it, will you switch to Bing? It's not hard to switch the default search engine in most browsers. It could be an interesting experiment.

What about DuckDuckGo? This is the new super-geek favorite. It prides itself on being secure, clean and objective. It's also customizable, and it launched a new redesign today to welcome disgruntled Google customers. But could it possibly be as comprehensive as Google? It hasn't lived up to that in my personal experience.

Whatever you decide, please share it with us at ReadWriteWeb. You can post it in the comments below or tell us about it Google+ or Facebook. We're still experimenting with the new features, and we want to hear how it's going for you.

While today's new social features are limited to the Spotlight section, it adds another way in which Google News can personalize content for logged-in users using their social data. Google is rolling out these kinds of Google+ features across all its Web properties.

Google Web search has treated public G+ posts as search results since soon after the social network launched. Google is insisting upon making its new social layer a pervasive, personalized filter for the whole Google experience.

It's all part of an effort to redefine relevance in the way Google crawls the Web. Instead of brute rankings of the Web's content, Google has decided that personal, real-time recommendations are more relevant to us. Do you agree?

With hundreds of millions of tweets per day, Twitter needs smart personalization algorithms to make sure its search results are relevant far beyond simple keyword matches. This acquisition will help Twitter keep the value of search inside its own properties.

Allon built the Orion search engine, a technology that pioneered relevance and related terms in keyword search, which was purchased by Google in 2006. Allon, who was still a doctoral student at the time, was hired by Google to implement the technology. Google announced the completed integration in 2009.

Last year, Allon left Google to found Julpan and continue developing new social search technologies. Allon says that Julpan's technology is still in the "early-alpha-stage," but acquisition by Twitter and integration into a platform will mark Julpan's next phase. Twitter has made Allon a director of engineering.

Twitter's Search History

In 2008, Twitter acquired some real-time search technology from Summize and eventually integrated it into its own site. Twitter and Google arranged to share real-time data in 2009, giving Google powerful access to social data and in turn driving Web searchers to Twitter. But that deal expired this summer and was not renewed. Google wants to personalize search with its own social signals from Plus, and Twitter needed to find its own social search solution. Today's acquisition of Julpan is a step in that direction.

The Importance of Social Search

Social search is an important market because it's the key to personalized relevance. Google and Bing are both deeply invested. Bing has Facebook integration, and Google has rolled Plus posts straight into search results, giving both search powerhouses all kinds of social signals. In fact, since Google indexes tweets, it's often a better way to search Twitter than Twitter itself.

Startups are also popping up that are completely dedicated to social search. Wajam recently added Google Plus to its arsenal of social tools, and its search bar brings personalization to all kinds of sites - like Wikipedia and eBay - not just Web searches. Moreover, there are all kinds of dedicated Twitter Search tools that provide much richer results and data than Twitter's own search bar. But with Ori Allon's expertise and Julpan's software under the hood, Twitter will try to regain its advantage with better relevance.

What do you think of personalized search results? Let's discuss in the comments.

For users logged into their Google Accounts, searches will now display public Google Plus posts from people in their circles as search results, right alongside web pages. If it's a link, for example, that link will show up like any other Web result would, but the person who posted it will be displayed underneath it, along with the date of the post.

Google launched social search in 2009 as a way of adding personalization to search results. Facebook's partnership with Bing puts a big squeeze on Google's ability to provide the most personalized results. But in response, Google has begun to roll out social search worldwide, along with its +1 button for voting up content, and the integration of Google Plus posts will now begin to bring your friends' names and faces into your search results, all using data controlled by the search giant.

Do you think this will improve your search experience? Let us know in the comments.

The latest battle in the land of search engines is social search - the addition of signals from social graphs to bring users increasingly personalized search results. To that end, Google has been working on its offering the longest, first introducing the idea back in 2009 when it launched in the U.S.

Today, the company announced that it is "bringing Social Search to more users around the globe" and that it has plans to bring its most recent social addition - the +1 button - with it.

Social Search had previously been an experimental feature before finally becoming official in February 2011. The feature takes users social connections from a number of different sites and uses them as a signal when returning search results. You have to be logged into your Google account to see the feature, which pulls results from social networks, friends' blogs and shared content. Take a look at an example result:

When Google rolled out the feature officially, it also added increased user control, which allows users to go to their Google profile settings and determine which accounts they want to include and which they don't.

Social search has been heating up recently, with Bing announcing this week that it would add Facebook as a major signal in its own search rankings - something that could certainly give it a leg up on Google.

If you haven't yet seen the feature, the following video gives a bit more of an explanation:

When you look at the numbers, there's no doubt that Google is the clear leader among search engines. But if recent moves by Google and Bing, in which both added social indicators to their search algorithms, are any indication, then social search could be the thing of the future.

We have to wonder then, if social search is indeed the next big thing, if Bing could have found some solid ground to stand on in taking on the big G.

In case you haven't noticed, Google and Facebook notoriously just don't get along, with the most recent scrap involving Facebook allegedly hiring a PR firm to smear Google's good name.

It seems clear by now that Google will likely be the last company on the planet to gain access to the wealth of social data held close by Facebook.

Microsoft, on the other hand, has been buddy-buddy with Facebook for some time now. Just yesterday Bing, Microsoft's top-tier and second place search engine, tied its search results to Facebook's massive social graph. According to an article in Fast Company, the addition of social to Bing's search results isn't going to end there. Stefan Weitz, director at Bing, told Fast Company that Microsoft has plans to bring in social signals from a host of other sites, such as Twitter, Yelp and more.

"There are more signals than just 'Likes,'" said Weitz. "There are tweets, check-ins--when I'm at Spur restaurant in Seattle, and I say it's the best lamb tartare and post that on Yelp, that's a signal as well. There's a world where all these social and personal signals--whatever you want to call them--are consumed and indexed and made sense of."

The question now is whether or not you think social search really is the all-important future and holy grail of accurate search results. If it is, then Bing could have a leg up on Google in the form of around 600 million avidly "liking" and constantly connecting users - something Google isn't likely to see any time soon.

After all, Microsoft just isn't angering the masses like it used to. It doesn't seem like that much of a stretch for Microsoft to bring in Twitter data. And besides, remember, Twitter is NOT a social network.

Which network would you want in your attempts to provide social search - the not very social Twitter or Facebook, the site with its "like" button on more than 2.5 million websites worldwide? We'd put our money on Facebook.

The most exciting news to come out of the release is that there will be a new Bing Bar with a "universal like button," the first of its kind. Users will now be able to like any page on the Web from anywhere, regardless if that site has a like button installed or not.

Bing search results will now show "liked results, answers and sites" by showing contents that friends have liked. It will also show personalized results by surfacing content that friends have liked from "deep within" search results to the top page. Around 33% of users click on the top link of search results with click-through results dropping precipitously going down the page and to subsequent pages. So, if your friend liked something that was buried on page 89 of the search results, Bing will in theory bring it to the front page.

Crowd Sourcing Search

Outside of friends, Bing is looking towards crowd sourcing the decision engine by using the aggregate of likes on the Internet and bringing them to forefront. Bing also apparently will have the ability to crawl Facebook Pages for what brands and companies are posting online.

It is not just pages though, Bing can crawl profiles too. According to the pulled blog post; "Now when people search for a specific person, Bing provides a more in-depth bio snapshot, such as location, education and employment details, to help them find the person they're looking for more quickly."

Google cannot do this because Facebook does not allow it. But, Microsoft has always had a good relationship with Facebook CEO Mark Zuckerberg and were one of the early investors in the social platform, so Bing gets to integrate Facebook basically as much as it wants. A lot of people have come to count on the fact that Google cannot crawl Facebook for privacy reasons so with Bings basically unfiltered access, it might be time to revisit those privacy settings within Facebook.

Other features include "shared shopping lists" and flight planners that help friends share ticketing information to look for the best deal. It will also help you find friends in different cities when you are traveling with a function called "friends who live here."

Ever since last summer, the Internet has been awash in rumors of a Google social network. First, it was "Google Me" and later it was "Google +1". Last September, however, Google CEO Eric Schmidt explained that the company wasn't working on a stand-alone social network, but rather the interweaving of social elements. ""We're trying to take Google's core products and add a social component," said Schmidt.

Today, Google is doing just that. The company is updating its Social Search feature, which it first launched in 2009, and bringing a tighter, deeper integration of social connections to Google Search.

Let's take a look at what these integrations will look like. First, there's the blending of social search results.

As you can see, the blog by Google's Matt Cutts is amidst other search results, rather than quarantined at the bottom of the page. It's a blog post that Cutts posted on his personal blog, which he links to on his Google profile. Next, you can see that search results will contain content that's shared, not created, by members of our social circle.

"Currently, Google social search is based on content your friends create," said Cassidy. "We're expanding that to content your friends share."

Next, we have the updated control over what you share and display on your Google profile.

As you can see, Google may find accounts of yours from around the Internet and suggest that you connect them. If you don't want to, however, you can make sure that the account is not publically connected.

So, Is This Part of 'Google Me'?

If the so-called "Google Me" is simply a social layer, then we'd have to say that this qualifies. Search Engine Land had an article this week about a report that found that Google Search personalization wasn't arriving at the expected results. That is, Google's personalized search wasn't acting based solely on previous search history and interests, it wasn't "subtle" as the company has promised, and it wasn't surfacing the long-tail results one might expect.

This, however, is personalization taken to another level. This is personalization in the form of looking at who you know, who you're connected to on various social networks, and ranking content according to who created it and who shared it. We were told that Google will even go a step further and look at content shared by friends of friends.

"All the content in Social Search comes from publicly available websites," explained a Google spokesperson. "For example, you can find content from a friend if that friend has created a Google profile and chosen to link publicly to other websites, such as Twitter or Flickr. You can also find content from public Picasa Web albums, public Buzz posts, and your own Reader feeds."

Your friends don't have to even have a Google profile for their content to show up in your search. If you're friends with them on Twitter and you connect your Twitter account, you can see what they share on Twitter in your search results.

Beyond the increased depth of these social results and how they're displayed, there's actually not much here that Google is doing any different than it has for the past two years. But it doesn't take much for a company like Google to have a big effect.

As Cassidy pointed out to us at the end of our conversation, Google's mission is "to organize the world's information and make it universally accessible and useful." A move to create another, stand-alone social network would seem like folly to some, especially with the company's track record when it comes to social. This move, on the other hand, feels just right. Gather the information and use it as yet another signal on what is relevant to your search.

Unlike other Twitter widgets that simply stream tweets in a timeline, Topsy's new module let publishers display only the most relevant and brand-safe tweets. The content will be filtered - profanity-free and language-specific.

Topsy touts the increased engagement rates from publishers using social content powered by these modules. As the content is filtered based on relevancy, Topsy argues that it will provide readers with a better experience (leading in turn to more time spent on the site, hopefully).

As Vipul Ved Prakash, Topsy co-founder and CEO says, "The launch of Topsy Social Modules furthers our position as the fastest growing and leading supplier of relevant realtime search results from the social web."

Indeed, Topsy points to the importance in not just the social web, but in how it dovetails with search. Rather than PageRank as being the sole marker of what's important, links from Twitter are becoming an increasingly important signal of relevance. And as Topsy powers the largest searchable index of Twitter data in the world, it makes sense that publishers would want to turn to it to power widgets on their sites.

And while the world may not need another widget, this new feature from Topsy does seem to provide one with content that's more useful - for both readers and publishers.

Richard MacManus recently covered the trends in e-commerce over the past decade. He noted that Amazon and eBay have dominated the online retail market with their model of using implicit user data to generate recommendations for others. Although this model will surely remain a centerpiece of the online retail experience, it may soon face competition as "social shopping" takes off.

What is social shopping? This is similar to the question of "What is social search," which I addressed previously by describing the three flavors of social search: what they are, why they're relevant and how they will help you search better. The Amazon and eBay model of online retail tapped into what I refer to as "collective social search." Social shopping, on the other hand, is more like "friend-filtered social search."

In social shopping, you see recommendations and reviews that your friends have shared. You see items that your friends have purchased or brands that your friends have shopped with. This matters a lot when you're shopping for a digital camera and are stuck deciding between three different models. Of course, the last 10 years' worth of people's purchasing histories and written reviews on Amazon may help you narrow your choice - if you can filter out the noise. But those reviewers are entirely anonymous to you, even though they may use a real name and have a rating history with the site.

The decision you are making, as with most decisions, will carry consequences going forward, which is a part of the reason why collective intelligence can't provide the necessary emotional "spark" in quite the way that a personal recommendation can. Patricia Mejia, a commenter on Richard's e-commerce trends post, explained why she wants this in shopping: "I want to be inspired, intrigued and entertained when I shop online."

Algorithms don't provide that emotion. But a recommendation from a friend just might.

Plus, users increasingly expect this, and the larger and more connected our networks become, the more powerful this social shopping model will be. What are the social shopping services that do this best today? (Hint: not Amazon.)

Sites like ProductWiki are devoted to product comparisons, but their user base is most likely not your peer network. ThisNext and Kaboodle lie closer to the intersection of social media and e-commerce. They are predominantly social networks dedicated to sharing products and personal reviews.

Kaboodle's user profile for "aplyler" closely resembles other social networking sites, and the site provides functionality for creating product lists, commenting on items and, of course, adding friends.

On ThisNext, users' recommendations are featured front and center on their profiles. Here, "rjax" has been promoted to "Expert Maven" because of her extensive collection of recommended items. Unfortunately, the collection's range is so vast that you probably wouldn't care about the Christmas ornaments if you liked her review of the Macbook art decal.

Thus, the limitation with sites like ThisNext and Kaboodle is that you, your friends and the products you're going to buy all exist on those sites. In other words, the sites are social shopping silos.

RunToShop, on the other hand, brings a distributed social networking model to social shopping. A small Finnish startup, RunToShop aims to bring social recommendations to you wherever you may be, and from the friends in your network who you trust.

This means that if you're shopping for golf clubs on Smart Golf, recommendations will be embedded on the site through the RunToShop widget. Currently, all user reviews are shown, but in the next release, recommendations from friends will be prioritized. (You can pull in your friends with Facebook Connect.)

RunToShop also integrates with Facebook. So, if Facebook is where you spend most of your time, you can browse product offerings and friends' recommendations directly through the RunToShop Facebook app.

Finally, its distributed social networking platform allows your product reviews to percolate out to other sites where those products exist. If your long-lost sister, for example, discovers one of these products through LinkedIn, she can view your recommendation right there.

Based on most of the services I've seen to date, including RunToShop, the implementation and user experience around social shopping still has a long way to go. In the meantime, keep this in mind the next time you're shopping for the right social shopping service: will it provide the emotional spark you need?

Guest author: Brynn Evans is digital anthropologist, design researcher and author who studies social interaction design and social search.

I've written previously about how social search won't replace traditional search, how social relevancy rank can be used to deliver good results, and why the concept of social search is a return to a familiar state rather than something to fear. Today, I'll get more specific about the three flavors of social search that will improve user search experiences.

Collective Social Search

"Collective social search" is similar in concept to the wisdom of crowds, in that search is augmented by trends shared on a network (a la Twitter Trends) or results ranked against the real-time buzz of a group. Why might this be useful? Well, in some instances, we can't immediately find the information we're looking for; and pooled, aggregated data from the collective may point us to new avenues that expand our discovery process.

As of yet, no major search systems are doing this very well - and we don't know what type of interface would be optimal for sharing this information. The Cloudlet plugin inserts tag clouds (based on keywords) into search results; but tag clouds are known to be more of a distraction than a utility. BingTweets has been touted as such a resource, but it really only offers Twitter and Bing results on two separate pages. OneRiot shows only collective data from the real-time stream, although it may be integrated with Yahoo! results soon. And we are still waiting to see how Google and Bing integrate the Twitter firehose into their traditional search results - as opposed to merely including them as additional document-like resources.

Equally important will be understanding when collective social data should be shared with users: while performing the search or after? And for which types of searches?

My research on search strategies begins to address this question. Collective guidance may be useful when users are exploring a search space, possibly because the search domain is not familiar to them (i.e. they lack knowledge of how to drill down to an answer), or because they are passively exploring a problem. I find myself doing this all the time when I prepare recipes to cook. I want to browse recipes from many different sources before I decide what my own recipe will consist of. I don't have a specific recipe in mind (it's not an urgent, active request), and therefore I don't necessarily know when I've found what I'm looking for.

That said, it's hard to determine from keyword strings how active or passive a user's search is; i.e. it may be quite difficult to determine the type of search they're performing or how far along they are in their search process ("exploring" or "narrowing"?). Furthermore, the utility of collective social data for mainstream consumers will be limited, mainly because it doesn't come from trusted sources, unlike "friend-filtered social search" (see next section).

Friend-Filtered Social Search

Friend-filtered social search is approximately what Google is doing with its social search experiment: providing social data that your peers, friends of friends and wider "social circle" have shared. This data could appear alongside traditional search results (as with Google) or be exclusive results from within your peer network (as with TuneIn).

This is useful if your friends have shared relevant links, blog posts or tweets about a topic that you're searching for. If you were gathering ideas about, say, "the future of the desktop," you would see thought pieces, write-ups and links to projects from the main search algorithm, as well as stuff your friends are saying about applications they've encountered recently. If you trust your friends, they may serve as reliable filters, pointing you to relevant information.

The three major limitations of this approach are:

1. Your friends may have no archived social content that's relevant (or available) to your query. Searching within your Facebook network quickly demonstrates this problem. For this reason, augmenting traditional algorithms with friend-filtered social data may be better, rather than relying exclusively on data from one person's small exclusive network.
2. Current implementations are limited to keyword matching; whereas, searches that retrieve related posts based on topic, theme or timeframe might expose a wider set of results and combat the niche-social-network problem. This approach would be computationally harder than keywords alone, and exposing enough of the appropriate context remains a problem (see next item).
3. Understanding the context in which a post or link was shared is important. Without this, keyword- and even topic-matching might not convey to the user the relevance of a search result. Google provides limited context at the moment (showing only how you know a user, the source of the post and a short snippet). More testing is needed to learn how much and what kind of context is appropriate for social search content.

Similarly there is the issue of when friend-filtered social search would be relevant during a search. My instinct is that it will be useful throughout a search and for many types of searches (it is, after all, just another type of search result). This is critically different from collective social search and collaborative search.

Collaborative Search (a.k.a. Question-Answering)

"Collaborative search" is when two or more users work together to find the answer to a problem. This could look like IM-based question-answering (a la Aardvark ), Yahoo! Answers (which is relatively passive and asynchronous) or over-the-shoulder two-person search. In all of these cases, people speak to each other using natural language, which is incredibly useful for open-ended queries (e.g. "What is 'design thinking'?") or queries about unfamiliar domains (e.g. law, health, business, depending on your background). Such conversations, even not real-time ones, can assist people who don't know the right keywords to use (what's known as the "vocabulary problem").

My research has looked at the benefits of question-answering and at people's processes and preferences during search. Many users report that they want to attempt to search on their own first, or don't wish to interrupt their colleagues before they have given it a shot independently. This suggests that early social support should be passive (as with presenting collective or friend-filtered social data).

But later in the process, if the searcher gets stuck on a problem, they often turn to a colleague for help. If systems had a way of identifying difficult queries or search-process inefficiencies, they could offer more explicit social support to searchers. Perhaps the system could identify a domain-specific expert from the user's extended social circle. Information that this person has shared could be presented to the user, or this person could be suggested as a resource to chat with or email (depending on availability and preferences).

It should be clear by now that these three flavors of social search are complementary. Each has its pros and cons and is appropriate for different kinds of searches and during different stages of the search process. A powerful "social search engine" would be "smart" by making use of all three, while also exploiting the value of traditional algorithms.

Photos by: Who Wants to Be?, Claudia Lim and brewbooks.

Guest author: Brynn Evans is a PhD student in Cognitive Science at UC San Diego who uses digital anthropology to study and better understand social search.

But social search is not something to be afraid of. It's really just an extension of behaviors that we're used to in the real world, brought online, thanks to the advent of real-time social computing.

First, people have sought help from others for search problems and information-seeking tasks for a long time. Prior to the Internet, this was our primary way of getting information. We either asked a librarian to help us find something or, prior to that, we spoke to each other to spread information and seek help. We can reasonably treat this current trend in social search as a return to that familiar state.

Secondly, social search is no scarier than the Web itself. Social search will not make you easier to find. If you're the type of person whose social network data appears in search results, then you're already incredibly findable on the Web. Your tweets may reach more people than you want, but this also means that your ideas will be exposed to a wider audience, extending your reach and influence and presumably improving your brand. As before, if your tweets are currently open to the public, you're already reaching more people than you know.

The very real issue of relevance, though, comes up when dealing with social search. Noise, false information and spam could dilute a set of search results and distract users from their quest. But spam is context-sensitive. Well-targeted ads aren't regarded as spam; in fact, many people don't even know the difference between Google ads and the main set of results. Same with search. A Twitter post linking to an article on diet supplements may be perfectly relevant in a query on "dieting tips and tricks" on Bing. In any case, finding spammers on Twitter should be relatively easy judging by the follower-following ratio or similarity of tweets.

Social search is also not a fad. It's an improvement on limited algorithms that only index static pages. Chris Messina and Jyri Engeström remind us that we're in a transitional state from a Web of documents (in which algorithms were sufficient for surfacing relevant data) to a Web of people (in which PageRank no longer captures what's happening right now or happening among your group of friends). Facebook COO Sheryl Sandberg reiterated this at the Web 2.0 Summit, saying that there is a "shift going on from an information economy to a social economy."

Social search is one mechanism for leveraging the value in this shift.

So, as you get used to how companies like Google and Bing implement social search, think about how your community of Facebook friends, distant acquaintances in your Google contacts, nearby friends from location-based services and publicly bookmarked items might help you search better.

Guest author: Brynn Evans is a PhD student in Cognitive Science at UC San Diego who uses digital anthropology to study and better understand social search.