Social Search still doesn't have a super-prominent place in the Google Search results pages, but make no mistake: This is a very big step. What's your portal to the Internet: Google's algorithmic search of the Web at large, or your social circle of people on Facebook? That's the battle for the future that Google and Facebook are waging now, and Google Social Search is a big move. Facebook search is nowhere near as good.

Last week we wrote about how social networking is fast approaching the importance of online of search in terms of Web traffic. One vision of the future, though, has posited that social and search won't remain separate forever.

Do you want to have your questions answered only via your friends and their online content? No, probably not. But do you want to have your questions answered without the input of your friends and their trusted content? You probably don't want that either. Google Social Search is a nice combination of search and social. Facebook's search is terribly weak in comparison. That's where the real competition is, not between Google and Bing or Yahoo.

One interesting caveat, of course, is that most people have friend networks on Facebook, not in Gmail or Google Reader. Your Facebook Friends aren't included in Google Social Search, as far as we can tell. Update: Limited information from Facebook may be included in Google Social Search if your friends have associated their Facebook profiles with Google Profiles. But after chasing the Google Social Search team around on the phone for 15 minutes and just getting a PR-answer about this, we're left to conclude that the rivalry is as heated as we originally reported. Murali Viswanathan, Social Search product manager sent this by email: "If someone links to their Facebook account from their Google profile, Social Search may surface that user's public profile page. These are the same public profile pages already available on a search of Google.com and other search engines today."

Give it a try and let us know what you think.

Worldwide, Internet users conducted over 131 billion searches in 2009. Every day, people over 15 around the world conducted about 3.6 billion searches. That's almost 25 million searches conducted per minute.

According to comScore, Internet users in the U.S. conducted the highest number of searches on the top 10 search engines in 2009. U.S. Internet users over 15 conducted over 22 billion searches last year, followed by China (13 billion) and Japan (9 billion).

Just yesterday, we reported that traffic analyst firm Hitwise's latest data shows that the traffic to social networks in Australia is getting to the point where it will soon surpass traffic to search engines. Judging from these numbers, even if social networks pass search in terms of traffic at some point, search still has a lot of headroom to grow and will continue to do so in the near future.

Bing's success rate is now over 75%, while Yahoo Search still leads among the top search engines with a 79% success rate. As Hitwise's Bill Tancer points out, though, it is important to note that portal search engines generally see simpler queries and more of these queries are navigational or brand queries. Inevitably, these searches tend to have a higher success rate, and while only 9% of the top 100 search terms on Google are brand or navigational searches, these types of searches account for 15.1% of all searches on Yahoo Search and 16.5% of all searches on Bing.

Maybe Measuring Success Rate Isn't the Right Metric for Bing?

It is important to remember that Microsoft's strategy with Bing, however, is to give users more info on the site so that searchers don't even have to leave Bing.com. Because of this, the Bing team probably wants to keep the success rate rather low. It would be interesting to see how many of the searches on Bing that Hitwise would qualify as unsuccessful were actually due to the fact that the user got the answer to a query right on the site.

To be clear, this update is for universal image results only - not Google Image search itself. "Universal" results refer to the search results you receive when doing a traditional search on www.google.com. Introduced back in 2007, the term refers to the combined search results from multiple verticals, including image search, news, video search, and the other specialized engines linked from the top of Google's homepage. With universal search, you only have to refer to one set search results page to see all the relevant information on a particular topic. The page serves as the jumping off point for whatever knowledge you're after - whether that's a photo, a video, the latest news, or just good ol' fashioned information.

The updated image search results represent a minor change to Google's interface and one that many mainstream users may not have even noticed. But every little tweak that Google makes is only done after extensive testing. In this case, the update allows for one more image to appear in the universal image results box. One image may not seem like a major improvement, but it could mean the difference between a user clicking through to see more or abandoning their Google Search altogether. (You would be surprised how quickly some users give up on a non-productive search. Forget refining queries, they just go elsewhere or stop their search entirely!).

Google Announcement's Timing Aimed to Deflate Interest in Bing

It's also notable that Google is announcing this change around the same time as Microsoft plans to make another announcement regarding updated features for Bing, the company's new search engine. Since its launch earlier this year, the Bing Search Team at Microsoft has been busy rolling out updates that have included things like a revamped mobile search, improvements to maps, integration with math engine Wolfram Alpha, Twitter integration, and a new visual search interface. As most of these announcements were made, Google would make an announcement of their own - for example, how they were planning on adding Twitter to their results, too. And when Bing announced Visual Search, Google posted to their blog about a Google Experiment called "Fast Flip" which lets you visually peruse print articles online.

There's no doubt that the timing of this latest, albeit minor, news about Image Search improvements has to do at least partially with the upcoming Bing announcement. Clearly, we have entered a new era of "search wars." As angel investor Ron Conway noted earlier this fall at the TC50 conference, this time war is a good thing: "I think the huge winner here will be consumers because competition breeds innovation, and this nice little battle between Google and Microsoft is fantastic for consumers."

Here are Google's and Bing's lists of top search queries of 2009:

Some of these are pretty straightforward (Twitter, Michael Jackson, Facebook), while others, like 'torpedo gratis' (which refers to a free SMS service) and 'tuenti' left us slightly puzzled at first. It is also interesting to note that a lot of these search terms in Google's list are basically just URLs (Twitter, Facebook, Hulu, dantri.com.vn).

Sanitized Lists

It's important to note that Bing's list was mostly scrubbed of obvious URL searches, so a direct comparison between Bing and Google is sadly impossible. Neither Google, Bing or Yahoo made lists of their actual top queries available this year. All we got so far are highly sanitized lists of "trending topics." While these reflect the current mood, they don't really give us a good idea of what people search for on a day-to-day basis.

Your Personal Top 10 in Google's Web History

If you have Google Web History feature turned on, you can find a list of your personal top queries of 2009 here.

Ask.com

Ask.com also just published its top questions of 2009 - though questions like "What is Miley Cyrus' phone number?" make us wonder about the validity of this list.

1. How much should I weigh?
2. How do I get out of debt fast?
3. How do I get pregnant?
4. What is Twitter?
5. What is Miley Cyrus' phone number?
6. What is the meaning of life?
7. When will the world end?
8. How long does marijuana stay in your system?
9. What are the symptoms of Swine Flu?
10. What time is it?

As we told you last month when discussing the program's early successes, Cashback works by giving users a certain amount of money back every time they search for an item and then buy it from a participating store. But some users have found the opposite to be true: Retailer cookies trigger jacked-up prices for some items, causing a phenomenon one man calls "negative cashback." How much do Bing users stand to lose? Read on, and brace yourselves.

Essentially, certain products from certain websites appear through a Cashback-enabled browser to be a certain price. Yet, if the same user visits the same site at the same time from a non-Cashback browser or machine (or if he deletes his cookies), the price is sometimes drastically different in a way that benefits the end user not a bit.

As one user very succinctly put it, "If I go directly to butterflyphoto.com, I pay $699 with 0% cashback. If I use Bing Cashback, I pay $758 with 2% cashback, or $742.84. Using Bing cashback has actually cost me $43.84, giving an effective cashback rate of -6.27%."

We did the same search, and we saw the same results. Here's our Bing Cashback screenshot from an Internet Explorer window:

And here's the same product on the same website in a Chrome tab:

As a side note, the blogger that alerted us to this issue had previously received a nastygram from Microsoft about his post on Bing Cashback technical issues.

So, what do we make of this issue? Is it a potentially scammy technical glitch? More importantly, how soon can it be fixed so innocent online shoppers aren't quietly swindled out of cash throughout the holiday season? Let us know what you think should be done in the comments - particularly if you've noticed this bug yourself.

However, nearly everything else about the new Android application is the same as its mobile counterpart, including its search verticals of "web," "images," and "buzz" which sit above Taptu's search box on the app's main screen.

The "buzz" section contains real-time results pulled from sites like Twitter and Digg as well as from other social sharing websites, blogs, and data pulled from select panel of internet users who have downloaded the OneRiot toolbar and are anonymously sharing their web-browsing data with the company. This aggregate information is actually the most prominent source of real-time data for OneRiot's search service. As of September of this year, OneRiot claimed to have 3 million active toolbar users out of the 20 million or so who have downloaded the toolbar to date. Meanwhile, they're indexing around 20,000 links from Digg and 5 million from Twitter.

It's this data which powers Taptu's "buzz" section where you can find breaking news and other currently "hot topics" being discussed on the web. And unlike Twitter's trending topics, for instance, OneRiot doesn't link to raw tweets but to the actual news stories and blog posts that are sharing the information.

The main Taptu homepage also links to these trending items by way of a tag cloud whose colorful blue bubbles take you directly to the buzz section when tapped.

If you're interested in trying the new Android application, you can download a free copy from the Android Market on your mobile phone. If you don't own an Android device (or iPhone), you can still use Taptu via its mobile website available at www.taptu.com.

Microsoft's Live Labs has been the source of a few interesting projects: a 3D photo-stitcher called PhotoSynth, a bookmarking service called Thumbtack (which was shuttered just this month). Typically, the UIs have been slick, but user adoption has lagged.

In short, datasets are organized as collections. Results can be as granular or as big-picture as the user desires, and correlations and patterns are easy to see and examine through powerful but simple visualizations. Imagine browsing through thumbnails representing Kiva loans, then sorting the loans by the different types of businesses they helped established. Or, on a nerdier note, think about riffling through decks of Magic: The Gathering cards, zooming in for larger-than-life detail of the card's artwork and then zooming out to see how each was related or linked to others in the set.

This probably reminds you - as it did us - a lot of Wikipedia. But imagine Wikipedia as an infinitely scannable, shuffleable, expandable, retractable, linked, and yet still detachable deck of digital cards; and then you have an inkling of how Pivot looks and feels.

Collections can be created by anyone, including third-party developers. Types of collections include simple, linked, and dynamic, which are each progressively more difficult to create. Developers are also encouraged to create collections from existing online datasets, such as the Internet Archive or data.gov.

It's very exciting, indeed; and it's available for Windows users only at the moment. Mac users, we're sorry. Why don't you go write some complaint letters on your beautifully designed, virus-immune machines? We'd love to rub it in some more by posting a few screenshots with gloating captions, but we're too busy trying to get this machine to stop being so Windows-y and just run the software

Right now, the service is invitation-only. We encourage you to Google around for your invite codes or check in here later to see if the kind folks at Live Labs have passed along any to us.

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.

Using the OneRiot API, Taptu's new homepage presents a mobile-friendly search engine interface complete with search box and verticals for searching just the web, images, and now, "buzz." Previously, the site included verticals for music and video searches too, but those have seemingly been done away with in an effort to simplify the interface.

The new "buzz" section is where you can find the real-time results. Here you'll find content pulled from sites like Twitter, Digg, other social sharing sites and the company's own panel of users who have downloaded the OneRiot toolbar and are sharing their web-browsing data in anonymous aggregate.

While Twitter is clearly a source of breaking news, we've always found it a bit odd that OneRiot includes Digg in its "real-time" search engine. We've never thought of Digg as anything near real-time - in fact, it pales in comparison to Twitter when it comes to the speed with which information spreads. With the immediacy possible on today's web, sites like Digg seem much slower - painfully slow at times - often taking hours on end to feature the news that had already been buzzing on Twitter for half a day.

That said, Digg and other social news sharing sites can sometimes unearth news that had been overlooked by major media outlets, especially when focused on a particular niche like technology. For example, just think of how many stories you read on someone's personal blog or Reddit and never saw anywhere else on the web. By tracking niche websites like these as well as Facebook, MySpace, Bebo, social bookmarking sites like Delicious and StumbleUpon, microblogs and URL-shortening services, Oneriot can discover links that may have otherwise gone unnoticed.

Taptu's new mobile search engine interface currently works on major touch-enabled devices including the iPhone, iPod touch, G1, Nokia N97 and 5800, and the BlackBerry Storm 1. The Taptu iPhone application will also be updated soon to include the additional functionality. You can test the new service yourself starting at 9 AM EST by pointing your mobile browser to www.taptu.com.

This is a strange story, but no one said the path to the future wouldn't itself be strange. So consider suspending your disbelief so you can see what Leapfish has to offer.

Leapfish searches for user queries across 25 different services, from Google and Yahoo to Yelp, Digg and some Real Estate sites. The service determines which sources are providing the most relevant results and constructs a search results page accordingly. If users love Leapfish enough to marry it they can turn on as many as 35 different widgets to interact with things like their Facebook and Twitter accounts on the Leapfish home page.

The design of the site and results pages are quite nice and the fundamental idea is a good one. But how could Leapfish already be set to bank $10 million in revenue this year?

The Pleasanton, California company says it has 100 employees; 50 are listed on LinkedIn and almost every one of them are in sales.

The sales pitch is this: Leapfish is small today, but the keyword prices that companies (like this lady) are paying will be a bargain if Leapfish can really grow. It's an investment, and as such it's a very affordable one. Some companies have already resold the keywords they bought from Leapfish for a profit, the company says.

One part of what's being invested in is, no doubt, a vision of the future. Check out this absolutely cathartic video the company made about the real-time web.

Unfortunately, in our tests Leapfish doesn't work very well. Search results are often off-topic, there are software bugs in some of the most basic parts of the site on the day of its grand unveiling and the compelling vision isn't that exciting in reality. Check out our 5 minute tour of the site to see what $10 million in ads have been bought against over the last year.

The Bing team also added a few new features to the generic mobile search. Users can now search for NFL teams and players and get real-time updates about games, stats and scores while a game is on. This feature is only available in the U.S.

In addition, Bing has implemented a flight search feature. You can now type in the airline code and flight number and Bing will return the latest gate information and departure and arrival times.

But Will Anybody Use It?

The new mobile interface for the iPhone and similar devices looks a lot better than the earlier version and is also more usable. Given that users can only switch between Google and Yahoo as their default search providers on the iPhone, however, it's questionable how many iPhone users will actually use Bing's mobile search.

Real-Time Web Crawling in the Future?

Although only briefly mentioned in the post, Google hinted that they may begin looking into other mechanisms such as PubSubHubbub, an open protocol that provides near-instant notifications of change updates. No further details were provided beyond the one sentence, but the announcement clearly shows that Google has seen the writing on the wall and knows that the real-time web is the future. This is one trend the company isn't planning to ignore.

The real-time web, heavily influenced by the speed of Twitter and other other rapid-fire social networking updates, has created a desire among internet users for faster access to information. This desire has, in turn, led to the creation of new real-time protocols such as the above mentioned PubSubHubbub and its counterpart RSSCloud. If Google began to use these technologies for scanning the web, their search results wouldn't just be updated faster - they would be updated in real-time. That means information would become available in the search results listings as soon as it was published to the web.

That, of course, would lead to a whole new series of challenges for the search engine - most notably, how to rank the real-time results? Given that Google's search algorithm has been built on top of the concept of PageRank, a way to determine the relevance of a website by what other sites link to it, ranking search results that are so fresh that there is an absence of links could prove a difficult feat. However, Google is already doing this to some extent now. Over time, the PageRank algorithm has evolved and can now reward sites with fresher, more fitting content and rank them higher than sites with more links on some occasions. And if anyone can figure out the proper algorithm for mixing in real-time content and ranking it appropriately along with static pages, it's got to be Google. In fact, we'll probably soon see exactly how they plan on addressing this issue, when they incorporate Twitter search results into their index, as announced last week.

...But Until Then, Google Delivering Faster, Fresher Results Instead

Although the PubSubHubbub mention may have been the most exiting part of the announcement, real-time search results aren't here just yet. In the meantime, we have to just be content with sped up results instead. The post advises website owners who are blocking Google's search bot software known as Googlebot from crawling their RSS/Atom feeds to unblock it via their robots.txt file. If unsure, webmasters can test their feed URLs with the robots.txt tester in Google Webmaster Tools, as the post recommends.

Yahoo Search continues its steady decline. Yahoo Search lost another 1% market share last month and has now lost a total of 5% since September 2008 when it still owned 18.8% of the market according to Compete. The total search volume on Yahoo was down 8% and Yahoo served 100 million less queries in September than August.

Google, Ask and AOL Hold Steady

Google's market share grew slightly from 72.3% to 72.6%, while Ask and AOL remained stable. Based on this data, Bing seems to be eating into Yahoo's market share, but isn't growing at Google's expense.

Searches Per Day

Compete's Marko Madjarac points out that Bing's numbers are even more impressive when we take into account that Bing's users tend to perform fewer searches on the service (5 searches per user per day) than Google's users (5.6 searches). Bing apparently lives up to its promise to get users to relevant answers faster than any other search engine. Yahoo users performed an average of 7.8 searches per day.

Both companies are hoping you'll come to their sites to search for what you're looking for, what people are saying about that topic and what your friends think. Microsoft is very much in the game, too. Here are some things to consider in this search war. It's a new fight - now including the real-time, social web!

The following is our attempt to piece all of this together, but the war rooms of each of these companies are no doubt buzzing trying to put together and understand the same details and more.

Google's new Social Search will allow users to opt-in to having search results from content created by their friends on social networks around the web included in Google search results. Those friend connections could come from any number of sites that you and your friends have listed in your Google Profiles - but it won't include Facebook. That means it won't include very much, unless Twitter and Google Profiles become a lot more integrated.

Microsoft announced today that Facebook status messages and other content from Facebook users with public profiles will soon appear in Bing search results. That's a huge change for Facebook. Bing also announced Twitter search integration, which is live now.

Google announced a deal with Twitter today as well. So Bing has Facebook and Twitter. Facebook has Bing-powered web search. Google just has Twitter, no Facebook search.

Right now Twitter search is probably much bigger than Facebook (unless you're Facebook serving logged-in users), because only a tiny portion of the much larger number of Facebook users have opted-in to making their Facebook activity public. But Facebook has an explicit agenda to change that. One reason for that is that more public Facebook activity makes deals like the one it made with Bing today much more valuable.

More now than ever, Google needs Twitter data to combat Facebook's social dominance - Facebook is five to ten times as big as Twitter today.

Microsoft would rather you did all your searching from Bing but it does own a meaningful portion of Facebook. You can bet it wishes it owned more.

No one is set to be the clear winner here, but with far more social activity and a multi-layered partnership with the first qualified web-search challenger to Google in years (Bing) Facebook may in fact have the strongest hand.

It's going to be a wild ride and big moves are being made right now.