Unlike Google's last big invite-only rollout of a social initiative - Google Wave - users will not be confounded on just what the heck you are supposed to do with the service when signing up for the first time. From Friendster, Friendfeed, MySpace and Facebook, users are familiar with how a social platform is theoretically supposed to look. At its core level, Plus is not that much different. Yet, there is so much more. How do you get started with Google Plus? Let's break down the nuts and bolts.

Editor's note: This story is part of a series we call Redux, where we're re-publishing some of our best posts of 2011. As we look back at the year - and ahead to what next year holds - we think these are the stories that deserve a second glance. It's not just a best-of list, it's also a collection of posts that examine the fundamental issues that continue to shape the Web. We hope you enjoy reading them again and we look forward to bringing you more Web products and trends analysis in 2012. Happy holidays from Team ReadWriteWeb!

Create Your Circles

Imagine the ability to break down Facebook into its various constituent parts and keep them separate from each other as opposed to one giant feed. That is what Google has done with Plus. There is one main stream where all your friends' updates show up, then you have the option to see updates from only certain groups like "Work," "Friends" or "Family." This is the essence of Circles.

From the initial interface, you will see four buttons - Home, Photos, Profile and Circles.

The first thing you are going to want to do is set up your circles. Click on the tab and it will bring you to a interface where all of your contacts in Gmail (not just Gmail addresses, but all of your contacts) are listed in a panel on top of the screen. Below is a panel that has your various circles. To add a contact to a circle, drag from the top of the list to the appropriate group. Contacts can be added to multiple circles.

One of the initial problems I had from the circles interface was that I added a couple of "Friends" into my "Work" circle and could not figure out how to get them out. You can do this from the user streams by hovering over the person's name and hovering over "Add to circles" and clicking the appropriate boxes. Yet, from the circles interface, that was not readily apparent. To take people out of a circle, hover above the circle, grab their icon and drag it back into the people plane.

One of the great differentiators between Twitter and Facebook is the "unbalanced" or "balanced" follow. Facebook was initially a two-way follow paradigm - I friend you, you friend me and we see each other's updates. This has been changed with the ability to "like" groups, brands and pages without them following you back. Twitter has always been a one-way follow - I follow you and you do not necessarily have to follow me back.

This line has been blurred in circles. If a person is in your contacts, they can be added to a circle and will get a notification that has happend (but not what circle they have actually been added to). There is also a "follow" circle. Just like Twitter, you can follow people and see their updates without them having to follow you back. As your circles evolve this could allow to track different interests, like Twitter lists.

The Stream and "Bumping"

Once you have set up your circles, go back to the Home screen to see the results. Below the profile picture you will see the choices of stream. You can view your entire stream at once (à la Facebook) or by particular circle.

There are two other options below your circles - Incoming and Notifications. Clicking incoming will bring you to messages that have been sent by people outside of your circles. Notifications will show you when people in your circles have commented on something you have posted, or something you have commented on.

Below the circles and notifications there is a tab dubbed "Sparks." More on that below.

One of the killer features of Gmail, or any Google product, is Chat. It has made its way into Plus and sits in the familiar left-hand, bottom-right portion of the screen that it is found in Gmail. Users with a lot of Circle and Chat contacts will like the ability to enable chat for particular groups. Want to surface friends and family but not acquaintances? Plus will let you do that.

If you are using Plus in a Chrome browser, desktop notifications do not pop up when someone sends you a message like it would in Gmail.

Posting a status update in Plus is not like sending a Tweet or updating Facebook. The core functions of an update are present - photos, links, video and location - but when you hit "share" it doesn't automatically post your message to everybody in your circles. You have the option to decide which circles your update is posted to, from individual groups to all circles, to extended circles, or just a single person.

An interesting feature in the user stream is that conversations will surface back to the top of the feed when subsequent comments are made on a thread. This, according to Google developer Jean-Baptiste Queru, is called "bumping." Google Buzz has this same capability and it was also a feature of FriendFeed.

Photos

Photos in Plus are relatively self-explanatory. Users can update photos from their computers or from their phones, see photos that people in their circles have uploaded. With the Android app, there is a way to upload any photo that you take with your phone straight to Plus, an interesting if slightly disconcerting feature.

When you add a photo, it will prompt you to create an album. Once that album is created it will ask which of your circles you would like to share it with. This is a prime differentiator from Facebook where all of your photos are visible to all of your friends by default (you can change who can view certain photos in Facebook preferences). You can also pick an individual to share photos with instead of an entire circle.

Photo uploading is easy within Plus. Just like adding a picture or an attachment to a Gmail document, you can drag-and-drop from your desktop or click the on the upload button and browse your computer for pictures.

Users can also add photos by posting them in status updates or by uploading them through the Profile tab.

Profile

If you use any Google products and have a Google account, you have a Google Profile. Profiles are unknown to most of the Internet because, until now, it was relatively useless to anyone but Google.

Your Google Profile is now the hub of you Plus experience, the backbone that everything else is built upon. There are six tabs in your profile page - posts, about, photos, videos, +1s and Buzz.

A significant change to your profile page is that there is now a location where your +1s live. Until now, when you clicked +1 on content on the Web, nothing happened. The information was sent to Google and integrated into some type of esoteric search algorithm. Users can now see what people have +1ed through their Google Profile. Unlike the Facebook share/like/recommend buttons, it does not go straight into your stream but rather to the profile page.

Sparks and Hangouts

Hangouts is a new feature rolled out with Plus. Essentially it is an area where your circles or a select group of friends can video chat all on one screen. To start a Hangout, go to the "Welcome" button in the home tab. It will prompt you to start a hangout and invite individuals or entire circles. Up to 10 people can be in a hangout at once and it will be seen in that circle or users' stream.

Sparks is the part of Plus where you can find content on the Web that you are interested in. In the "Field Trial" version of Plus, it looks like Sparks is a randomized version of content and news generated through Google News. Sparks can be a dashboard for things you are interested in on the Web. When you do a search in Sparks, it will predict what you are searching for with a drop down menu (like old Google search, not quite like Google Instant). You can pin particular topics you search for to the Sparks dashboard for quick access.

You can share articles found in Sparks with a share button on the bottom of every article that surfaces in a search. Like everything else in Plus, it can be shared with a specific person, circle, group of circles or the general public.

For more information, check the videos that Google made explaining Plus and all of its aspects -- Circles, Hangouts and Sparks.

Amid the continued growth of these social networks, there has been much excitement about how the rest of the Web would soon be infused with all things "social": social search, social commerce, social deals and more. And yet the effort to socialize the rest of the Web has so far failed to live up to its promise. Why?

Facebook's master plan, articulated by founder Mark Zuckerberg, was that once its site had built a map of everyone you've met or known, you would be able to leverage that information across the Web, to see what your "friends" are searching, buying, watching, liking or saying.

Since 2008, Facebook has attempted to roll out this strategy by using "Facebook Connect" to extend its social graph into millions of other websites, and by incorporating new functionality into its own site. Yet many of the most anticipated social integrations so far have failed to take off:

• Social commerce: When Delta Airlines launched a Facebook "ticket window" last year, it was seen as the future of e-commerce, with every ticket purchase shared socially to the customer's friends. Yet, one year later, nearly all of us still buy our tickets on dedicated airline or travel sites.
• Social search: When the Bing search engine started highlighting Web pages that the user's Facebook friends "liked," it heralded the arrival of a long-awaited "social search." Yet, the fraction of "liked" pages was so tiny that the social feature was nearly invisible.
• Social deals: When Facebook moved into the daily deals space, it was seen as a potent challenger to Groupon. But four months later, Facebook announced it was closing its local deals business.
• Social viewing: When Facebook offered its first streaming movie this spring, on a Time Warner Facebook app, it was heralded as an opportunity to make movie viewing social. Yet, this experiment failed to produce much customer interest.

At last week's F8 conference, Facebook unveiled much more ambitious efforts to integrate outside web brands into its site - from a full-fledged Netflix movie player, to a music player drawing on Spotify and several other streaming music services.

But for any of these, or other social integrations to succeed, Facebook and its partners and rivals will need to learn from past mistakes. To date, their vision of how to make the Web more social has been based on a fundamental misunderstanding of our digital behavior.

Understanding Social Graphs vs. Interest Graphs

In order for social networks to truly reshape our experience of the rest of the Web, developers must first understand the relationship between our social graphs and our interest graphs.

A social graph is a digital map that says, "This is who I know." It may reflect people who the user knows in various ways: as family members, work colleagues, peers met at a conference, high school classmates, fellow cycling club members, friend of a friend, etc. Social graphs are mostly created on social networking sites like Facebook and LinkedIn, where users send reciprocal invites to those they know, in order to map out and maintain their social ties.

An interest graph is a digital map that says, "This is what I like." As Twitter's CEO has remarked, if you see that I follow the San Francisco Giants on Twitter, that doesn't tell you if I know the team's players, but it does tell you a lot about my interest in baseball. Interest graphs are generated by the feeds customers follow (e.g. on Twitter), products they buy (e.g. on Amazon), ratings they create (e.g. on Netflix), searches they run (e.g. on Google), or questions they answer about their tastes (e.g. on services like Hunch).

Photo by duchesssa

Next page: The Fallacy of Social Web 1.0

The Fallacy of Social Web 1.0

The fundamental stumbling block of the social Web to date is that it has conflated social graphs with interest graphs. But in reality, who you know does not always translate into what you will like.

For example, I have a particular taste in movies. But I do not share that same taste with most of the people whom I have friended on Facebook - a motley mix of high school classmates, work colleagues, PTA committee members, and fellow jazz buffs. Nor do we, as a large and heterogeneous group, all share the same taste in travel, or fashion, or much of anything else. So when Facebook attempts to improve my movie-viewing experience by revealing the tastes of everyone in my entire social graph, the value to me is quite low.

The Future of the Social Web: Integrating the Graphs

So far, the job of mapping users' social graphs has been taken up by social networking sites like Facebook and LinkedIn. Meanwhile, interest graphs have been best built by e-commerce sites such as Netflix and Amazon that focus on highly customized recommendations.

The future of a truly social Web will rely on getting these two types of graphs to work together. We are just starting to see some interesting attempts at this:

• Social circles: On Google+, users explicitly place each member of their social graph into one or more "circles" based on common interests and the type of content they want to share with them. In response, Facebook has just re-launched its own feature to manage social circles.
• Feed lists: Twitter's lists feature allows users to create sublists of people and brands to follow based on different topics (e.g. news headlines, favorite celebrities, fellow sports fanatics, or authors you admire).
• Single-purpose graphs: Niche services aim to map out just one particular circle of shared interest, such as micro-social-network Path (for mapping your 50 closest friends), or social music site Turntable.fm (for sharing playlists with likeminded music lovers).

In the near future, we should see new and better solutions to integrating social and interest graphs.

For Now, Pick the Right Graph

Until this kind of integration is achieved, though, Web services should consider carefully when to utilize the customer's social graph, and when to use their interest graph.

Then the service should pick the graph that adds value to the customer experience. Because the real social Web will be all about the customer.

Facebook seems to be testing a new feature that could give it more granular data of people's profiles and strengthen bonds within its social graph. Facebook has started showing users a "needs review" notification for information that others add in your profile. For instance, say you want to add a colleague from a past or current job, the person gets a notification that says that there is information that you need to review.

In terms of employment, this brings Facebook much closer to LinkedIn's style of strengthening connections along its social graph. LinkedIn makes it very clear that you must have a connection with the other person and the connection must be approved by both people before the link is completed. In this way, Facebook can make stronger ties in the vast web of its social graph.

How To Use The New Facebook Lists (And Why You Should)

Facebook's Subscribe Button & Public Social Networking

Facebook Releases Smart Friend Lists to Counter Google+ Circles

Does Facebook's Subscribe Button Betray What the Company Was Built On?

Prompting Users To Strengthen Ties

What Facebook really wants to do is hone in on the most granular connections it can make amongst its users. Think of it as a wheel with spokes. A particular user is the center of the wheel. The spokes coming off the center are the strongest connections that person has in their social graph. That could be a significant other, work connections, family, close friends you associate with frequently etc.

Facebook can then work off this map they have created of your life. Ostensibly, this would be for the means of advertising and targeting. For instance, if Facebook knows where you work and the people that work there with you, it can more efficiently target ads or services (like games or apps) that are likely to be of interest. For instance, Richard and I work for ReadWriteWeb (well, I work for Richard at ReadWriteWeb). Facebook knows that RWW is in its tech/media categories. Ad buyers looking at Facebook's platform could theoretically buy a block of advertising that is targeted at people who specifically work in tech media. The stronger the ties that Facebook makes in users' social graphs, the more of a premium it can put on targeted advertising. Or push users to a particular service that is beneficial to Facebook such as generating more data or purchasing a product.

Consolidating The Social Graph

Under Facebook's older versions of its social graph, this particular data was not readily aggregated. Yet, by getting one person to confirm the connection, the work on Facebook's side is eased tremendously. The users are strengthening the connections themselves as opposed to Facebook having to extrapolate from their own data that two people may be connected in one fashion or another.

Where LinkedIn works so well is that it is in the particular market of employment. It can hone its data in on certain professions or verticals through information the users provide themselves. This is a step by Facebook in that direction.

This is all a function of the new subscribe button and smart lists features. What happened in this particular instance is that I added Richard to my ReadWriteWeb smart list that Facebook automatically generated for me. Under the hood, Facebook must have extrapolated that both Richard and I list RWW under our employment. It then automatically sent a message to Richard to confirm what its own data was telling it.

Facebook's power is its wealth of data within the social graph. In recent weeks we have seen Facebook begin to consolidate that power by adding context to much of its data. It is doing this automatically on its side by making connections between users (smart lists) and now it is having users themselves create the strong connections ("needs review" and the subscribe button).

Have you seen the "needs review" notification pop up in your Facebook profile yet? Is the strengthening of ties in your social graph beneficial to you as a user? Or has Facebook become too clever for its own good?

Unlike Sonar or Foursquare, where you have to go outside the app to Twitter to talk to people or leave time-delayed comments on check-ins, Blendr keeps your interaction with nearby people in the same app.

Keeping that kind of experience within the same app is what Blendr is hoping to capitalize on. Apps that do not rely on pushing people out to third party apps to complete the communication and connection circuit is a move all location based services will have to make. Think of it as a brand experience, the kind of thing that nurtures consumers' trust for a brand.

The app is well designed, with a compelling UI. But it has bugs. Here's what I found after trying it: you key in your interests, you browse for users by location, your favorites, those you've chatted with recently or those currently online - but the chat feature didn't work. It kept saying I was offline. The whole thing failed, in that regard. It does have going for it a very deep set of subcategories to use to label your interests, but I was only able to choose seven for some reason.

I'm more interesting than that.

For starters, it looks more cohesive. This isn't surprising because it is a blank slate product that did not have to deal with the technical debt Facebook has accumulated since 2004. Beyond the interface however, Google Plus will be more engaging emotionally for people because it allows them to be more authentic with one another.

Why? Because Google Plus establishes intuitive clarity for my social graph.

It allows me to explore the full spectrum of emotions within an engagement because I know exactly who I am sharing it with, and in what context (conversational or informational). It fosters deeper, more significant bonds irrespective of distance.

Google Plus enables connections to become experiences between people. Well done Google, you now have a weapon that can be strategically propagated amongst the 1 billion unique users who visit your properties every month.

Pundits all over speculate that Google Plus is too little, too late, that Facebook owns the social graph and with it, the future of the Web. I disagree. Superior experiences coupled with network effects, prevail over time. Just ask Mark Zuckerberg circa 2007.

Is Google Plus special enough to warrant that consumer shift? Not yet. Google has shown courage under fire here; and as the stellar article in Wired showed - it is willing to be patient. But for it to prevail against Facebook, it is going to have to be daring. Qui audet adipiscitur.

Here's three ways it can dare to win.

Go Beyond The Walled Garden Experience

I don't want my social engagement to be constrained to my "circles" or "friends". I want spontaneity too, allowing me to engage in serendipitous conversations with others based on a specific interest or motive. I don't always know someone's email, but I can discover their Twitter handle. So why can't I invite them to a Google Plus Huddle or Hang Out via my own Twitter account? I may put them in a circle once I know them better or I might not. Either way, I want the ability to engage new and interesting people from Google Plus!

Let Me To Have Ephemeral Interactions With People

As Google's social lead Vic Gundotra astutely noted, human relationships are nuanced and transient. By extension, so this the information we share with others. So why don't I have the ability to engage someone off-the-record, with assurance that data from this temporary interaction isn't saved on Google's servers nor is it retained within my browser cache? People have real-world interactions of that kind all the time!

I see you at a conference, we discuss, we disperse. All we are left with is a memory of the experience. I am not saying every interaction should be temporary - just ones where we desire that extra level of discretion. People will appreciate that degree of empowerment. Most importantly though, it is one more signal for Google Plus' algorithms to gauge strength between relationships.

Use AI To Augment Me, But Don't BE Me

In the Wired article, Gundotra says, "We think long-term, four to five years from now, the system should be putting items in there not just from your friends, but things that Google knows you should be seeing."

That statement is disturbing on two levels. Firstly, it is general consensus that Google has the most formidable artificial intelligence talent on the planet (Exhibit A) honing their skills on one of the richest data sets imaginable. It is their one asymmetric advantage against Facebook - so why would you wait four years to leverage it? They already leverage predictive analytics brilliantly inside Gmail with the "consider including" feature and in Reader with their "sort by Magic" feature.

The only conclusion I can make is that they are still hurting from the Buzz debacle and are trigger shy. Second, I don't want Google "putting" items into my feed. Show me a bunch of super-intelligent recommendations that I might consume, that I might share, that I might engage with and you have made my day more interesting. There is a narrow line between between helping me and being me. Don't blur it.

Google you have the talent, courage and patience to take the fight to Facebook; Google Plus is ample evidence of this. But will you dare to win?

Unlike Google's last big invite-only rollout of a social initiative - Google Wave - users will not be confounded on just what the heck you are supposed to with the service when signing up for the first time. From Friendster, Friendfeed, MySpace and Facebook, users are familiar with how a social platform is theoretically supposed to look. At its core level, Plus is not that much different. Yet, there is so much more. How do you get started with Google Plus? Let's break down the nuts and bolts.

Imagine the ability to break down Facebook into its various constituent parts and keep them separate from each other as opposed to one giant feed. That is what Google has done with Plus. There is one main stream where all your friends updates show up then the option to see updates from only certain groups like "Work," "Friends" or "Family." This is the essence of Circles.

From the initial interface, you will see four buttons - Home, Photos, Profile and Circles.

The first thing you are going to want to do is set up your circles. Click on the tab and it will bring you to a interface where all of your contacts in Gmail (not just Gmail addresses, but all of your contacts) are listed in a panel on top of the screen. Below is a panel that has your various circles. To add a contact to a circle, drag from the top of the list to the appropriate group. Contacts can be added to multiple circles.

One of the initial problems I had from the circles interface was that I added a couple of "Friends" into my "Work" circle and could not figure out how to get them out. You can do this from the user streams by hovering over the person's name and hovering over "Add to circles" and clicking the appropriate boxes. Yet, from the circles interface, that was not readily apparent. To take people out of a circle, hover above the circle, grab their icon and drag it back into the people plane.

One of the great differentiators between Twitter and Facebook is the "unbalanced" or "balanced" follow. Facebook was initially a two-way follow paradigm - I friend you, you friend me and we see each other's updates. This has been changed with the ability to "like" groups, brands and pages without them following you back. Twitter has always been a one-way follow - I follow you and you do not necessarily have to follow me back.

This line has been blurred in circles. If a person is in your contacts, they can be added to a circle and will get a notification that has happend (but not what circle they have actually been added to). There is also a "follow" circle. Just like Twitter, you can follow people and see their updates without them having to follow you back. As your circles evolve this could allow to track different interests, like Twitter lists.

The Stream and "Bumping"

Once you have set up your circles, go back to the Home screen to see the results. Below the profile picture you will see the choices of stream. You can view your entire stream at once (à la Facebook) or by particular circle.

There are two other options below your circles - Incoming and Notifications. Clicking incoming will bring you to messages that have been sent by people outside of your circles. Notifications will show you when people in your circles have commented on something you have posted, or something you have commented on.

Below the circles and notifications there is a tab dubbed "Sparks." More on that below.

One of the killer features of Gmail, or any Google product, is Chat. It has made its way into Plus and sits in the familiar left-hand, bottom-right portion of the screen that it is found in Gmail. Users with a lot of Circle and Chat contacts will like the ability to enable chat for particular groups. Want to surface friends and family but not acquaintances? Plus will let you do that.

If you are using Plus in a Chrome browser, desktop notifications do not pop up when someone sends you a message like it would in Gmail.

Posting a status update in Plus is not like sending a Tweet or updating Facebook. The core functions of an update are present - photos, links, video and location - but when you hit "share" it doesn't automatically post your message to everybody in your circles. You have the option to decide which circles your update is posted to, from individual groups to all circles, to extended circles, or just a single person.

An interesting feature in the user stream is that conversations will surface back to the top of the feed when subsequent comments are made on a thread. This, according to Google developer Jean-Baptiste Queru, is called "bumping." Google Buzz has this same capability and it was also a feature of FriendFeed.

Photos

Photos in Plus are relatively self-explanatory. Users can update photos from their computers or from their phones, see photos that people in their circles have uploaded. With the Android app, there is a way to upload any photo that you take with your phone straight to Plus, an interesting if slightly disconcerting feature.

When you add a photo, it will prompt you to create an album. Once that album is created it will ask which of your circles you would like to share it with. This is a prime differentiator from Facebook where all of your photos are visible to all of your friends by default (you can change who can view certain photos in Facebook preferences). You can also pick an individual to share photos with instead of an entire circle.

Photo uploading is easy within Plus. Just like adding a picture or an attachment to a Gmail document, you can drag-and-drop from your desktop or click the on the upload button and browse your computer for pictures.

Users can also add photos by posting them in status updates or by uploading them through the Profile tab.

Profile

If you use any Google products and have a Google account, you have a Google Profile. Profiles are unknown to most of the Internet because, until now, it was relatively useless to anyone but Google.

Your Google Profile is now the hub of you Plus experience, the backbone that everything else is built upon. There are six tabs in your profile page - posts, about, photos, videos, +1s and Buzz.

A significant change to your profile page is that there is now a location where your +1s live. Until now, when you clicked +1 on content on the Web, nothing happened. The information was sent to Google and integrated into some type of esoteric search algorithm. Users can now see what people have +1ed through their Google Profile. Unlike the Facebook share/like/recommend buttons, it does not go straight into your stream but rather to the profile page.

Sparks and Hangouts

Hangouts is a new feature rolled out with Plus. Essentially it is an area where your circles or a select group of friends can video chat all on one screen. To start a Hangout, go to the "Welcome" button in the home tab. It will prompt you to start a hangout and invite individuals or entire circles. Up to 10 people can be in a hangout at once and it will be seen in that circle or users' stream.

Sparks is the part of Plus where you can find content on the Web that you are interested in. In the "Field Trial" version of Plus, it looks like Sparks is a randomized version of content and news generated through Google News. Sparks can be a dashboard for things you are interested in on the Web. When you do a search in Sparks, it will predict what you are searching for with a drop down menu (like old Google search, not quite like Google Instant). You can pin particular topics you search for to the Sparks dashboard for quick access.

You can share articles found in Sparks with a share button on the bottom of every article that surfaces in a search. Like everything else in Plus, it can be shared with a specific person, circle, group of circles or the general public.

For more information, check the videos that Google made explaining Plus and all of its aspects -- Circles, Hangouts and Sparks.

LinkedIn showed off a new addition to its Lab site today called the LinkedIn Connection Timeline. It's a very fun way to remember people you used to work with throughout the years - and see where they are now. Built internally by LinkedIn's Gordon Koo, the visualization does a good job illustrating the tip of the iceberg of what structured, social data can provide when accessed programmatically.

And it's fun. It brings to mind the app Memolane and makes me wish someone would build something like this for Twitter or Facebook. Take the list of people I'm connected to there and show me when on a timeline I connected with the ones I have interacted with the most. Play me a song that my Last.fm profile says I used to listen to a lot, don't listen to anymore and that has a high-emotion rhythm to it and you've got a mashup that could bring lots of people near tears. (You just know that Facebook will offer something like this someday.) Always more emotionally reserved, LinkedIn at least offers a fun retrospective of past co-workers.

Professional social network LinkedIn has opened up access to a new developer platform today that should bring LinkedIn content, buttons, Twitter-esque "profile summaries" and more to websites throughout the Web.

The platform, though, isn't just for developers. LinkedIn is offering an entire suite of plugins to bring all of this content to your website. Even better, it's making it as easy as the click of a button and it could offer some serious competition to Facebook's Open Graph on sites that cater to the career-minded.

On top of buttons for sharing websites and recommending products, LinkedIn is offering a set of plugins to display profile summaries, full profiles, company profiles and "company insider." This last plugin shows customized information about a company including who, in the logged-in person's network, works there, a list of new hires and job changes, and even the ability to follow such news. That's the other big offering - a LinkedIn login that supports OAuth 2.0.

The ease with which these features can be implemented will likely be the most exciting point for many non-developers. The plugins take a couple lines of code that can be copied and pasted into a site's code. All you need to do to get a plugin is go to LinkedIn's plugin gallery (as seen below), click on the "Get It" button and paste the code into the site.

Beyond ease of implementation, LinkedIn says that it has also made "significant infrastructure improvements to the platform itself," improving the JavaScript load-time and adding SSL and more robust OAuth support.

With the ability to easily add functionality like hovercard-esque LinkedIn profile summaries and company profiles, we'd be surprised if we didn't start seeing more LinkedIn content around the Web. Just as TechCrunch displays information about the companies mentioned in its article pulled from CrunchBase, other blogs and sites could now display LinkedIn information, which has the advantage of being fully interactive with the viewer's LinkedIn profile. While someone may not want to login to certain sites using their Facebook identity, this and the potential interaction with LinkedIn data and social graph could boost LinkedIn's presence on the Web drastically.

What do you think? Will the lure of profile summaries, company information and customized company profiles get you to second guess your login of choice on some sites? And how many sites will abandon Facebook to bring in the LinkedIn social graph instead?

This has led more technologists including myself to start thinking about how the Web needs to evolve to keep up with user expectations. People hold companies to impossibly high expectations to deliver extremely personalized experiences as they browse, shop, learn and play on the Web.

What we need is to build a smarter approach that allows companies to adapt to their customers' needs in real-time.

The concept of collective intelligence, which I'll address a little further down below, will be critical to achieving this vision--something I like to think of as an "adaptive Web." That is, a digital experience that is always relevant and based on users' current intent and interests. It also must be device-agnostic, especially important given the increased mobility of the online experience -- a challenge analyst firm Forrester calls "the Splinternet."

In an adaptive Web scenario, the Web will truly come to life and become self-learning. We'll see the Google way of determining linkages between sites and content go by the wayside in favor of an approach that's based entirely on what the Web community at large and like-minded users within it found useful.

An adaptive Web experience would represent a dramatic shift in how we interact with the Web (or more accurately, how the Web interacts with us). Let me explain.

What An Adaptive Web Would Look Like:

Let's say you're planning a trip to Vail with some old college buddies. So you hop on to Expedia to buy plane and hotel tickets. On checkout, you're suddenly alerted to a winter jacket sale at REI.com based on the Web community's affinities between Vail and buying ski jackets. No hard coding necessary.

After you get your jacket you then visit the Vail Ski Resort homepage, which is automatically optimized to show you the best trails because it knows you're already headed there (and thus need no persuading why Vail is the best place on Earth to visit!). Later that night you search for "Sushi in Vail" on your iPhone and the top search results are all restaurants by your Vail hotel that are open on the days of your trip.

This is just the tip of the iceberg. At some point, we could see a time when not only your Web experience is adaptive, but also your social connections - based merely on your current intent and interests. For example, in the scenario above you could also be temporally linked with people who are going to Vail at the same time or who live in your area. This would have numerous benefits: you could share travel trips, ask them to carpool with you to save gas, or meet up for sushi at that restaurant you just discovered.

But creating an experience like this requires much more than machine learning and advanced algorithms. It requires a deeper understanding of how the human brain works.

Next page: Changing the Status Quo: No Easy Task

Changing the Status Quo: No Easy Task

To no surprise, there are numerous technical and psychological challenges for building an adaptive Web. Namely, I see three primary roadblocks:

1. Privacy Issues: To deliver adaptive experiences, we have to pay attention to what people are doing online in the first place. Different users have varying levels of comfort. We'll have to find some sort of middle ground where the value of an adaptive experience greatly outweighs users' privacy concerns.
2. Deciding on the Method: Second, there's determining the approach itself. Do we need a "metalayer" over the web? Some sort of toolbar or plugin that could connect users' entire Web experiences across devices? Do ISPs need to get involved at the network level to watch every site users' visit and how they engage with it? These are all options to consider - some more realistic than others - but the path is murky at best at this point.
3. Determining Users' Intents: The third obstacle is the biggest obstacle of all: pure science. It's not a trivial problem to automatically pinpoint and serve up an experience based on a user's current intent and context. As someone who has devoted his life's work to studying human/computer interaction, I can't emphasize this enough. Predicting what people want and need, and adapting their Web experience in real-time is perhaps one of the remaining "big picture" challenges facing technologists.

The good news is that we're not starting from scratch. In many ways, Amazon and recommendation engines were really the beginning of the adaptive Web, but because they were completely relegated to sidebar widgets on individual sites and leveraged only a small subset of users' implicit behavioral signals, they stopped short of delivering a truly end-to-end personalized and relevant Web experience.

The DiggBar hinted at the creation of browser/machine-agnostic Web "metalayer" but as we know that did not end well. The behavioral targeting guys of today have the right spirit, but their focus is on individuals' previous behaviors and the often-hardcoded needs of the seller rather than the dynamic needs of the buyer, which make it unlikely they'll be the ones rising to the challenge.

The Power of the Collective

Let's revisit collective intelligence and its role in making the adaptive Web a reality. Collective intelligence refers to the process of gathering insight from a group of like-minded individuals online, often implicitly based on their shared navigation and engagement patterns. A central concept of collective intelligence is to aggregate behaviors of the silent majority of website visitors, augment that information with the expertise of super-users and provide the most relevant information that meets every individual user's goals.

An obvious benefit to using collective intelligence to power the adaptive Web is one of mere scale: it enables machines to draw conclusions about an individuals' current intent based on the knowledge and experiences of the larger community. It also gives us the power to efficiently deliver automated and real-time experiences to users. This would be very difficult within any user-by-user scenario, which again poses enormous difficulties in matters of scale.

The Adaptive Web: Not If But When

Despite the obstacles I discussed earlier, I would argue that we're on the path to moving toward an adaptive Web - and at a rapid rate. The days of programmers organizing the Web and creating linkages and associations for us are ending, and the age of the self-organizing, adaptive Web is quickly approaching.

In many ways, it's in step with the democratization of the Internet: In the first phase of the web, only people "in the know" could publish content. In web. 2.0, everyone could explicitly contribute to the community via social networking and self-publishing tools.

Naturally, the next step is for all users to be able to contribute to building and organizing the Web in its entirety, organically shaping our individual relationship with it based on our collective experiences.

Do you agree? What do you think will be the biggest technical, if not cultural challenges in realizing an adaptive web?

Photo by waterlamd

Klout data is valuable because marketers, PR people and others want a way to quickly prioritize which Twitter users they should respond to among many mentions of a monitored brand. Twitter is uniquely well-suited to programatic analysis of topical influencers, as it is rich with interlinked, publicly accessible user profiles.

Klout said tonight that more than 750 companies are currently using its Application Programming Interface (API) to incorporate Klout scores into their software. Virgin Airlines, for example, used Klout scores to offer free flights this Summer to highly influential Twitter users.

The down side of such products may include that their analyses can be a black box, can depend on a variety of arbitrary decisions and potentially, that they facilitate elitism in an ostensibly democratic social media world.

"Phil will be overseeing our product with a focus on making the Klout score rock solid from a data perspective and that we continue to establish ourselves as the standard measurement of influence," Klout founder Joe Fernandez wrote tonight.

While it's surprising that dating services are the most detested among Facebook ads, it does make sense. Dating ads can tend to be some of the most transparent of advertisements online, especially on a site like Facebook, which has info about your sexual preference, age and location, depending on privacy settings. Though the ads are trying to create a personalized experience, when users see ads for meeting singles in their town within their age range, the ads seem intrusive and creepy.

There also may be a correlation between how users approach Facebook and their distaste for dating site advertisements. From my personal experience with online dating and matchmaking sites, I can attest that your activity on the site is not something you tend to share with many of your friends. With Facebook's recent concerns over privacy, users may be afraid to associate their online dating activities with their personal social graph on Facebook.

The survey by Inside Facebook also found that advertisements that linked to sites outside of Facebook were less liked by respondents. Nearly two-thirds said they dislike ads for outside links the most as opposed to links to Facebook fan pages or events. An advertisement for Coca-Cola, for example, is preferred when it is an add for Coca-Cola's fan page, not for an outside site run by the company. Perhaps dating sites need to advertise their fan pages, but something tells me that wouldn't go over well either.

In a hyperlinked world, where our activities, interests and social connections are naked to the world by interlinked web document, the factorial of that number of connections represents the universe of possibilities for analysis, feature development and added value.

Is this just the tip of the iceberg for Twitter? Should third party app developers be concerned that Twitter is slowly going to replace popular add-on features with tools of their own? It wasn't long ago that Twitter snatched up atebits, developers of the Tweetie iPhone app, which has since been rebranded as Twitter's official app. As Twitter expands it's base functionality to include more tools, some third-party developers may be nudged aside.

It is unlikely, however that Twitter would go to the trouble of over-developing on its own platform. Twitter has prided itself on its simplicity since its launch, and by creating too many tools it could ruin that delicate balance of simplicity and functionality. This is precisely why the mutual follow feature, like many before it, is being tested on a small sample size before being rolled-out to the entire population of users.

The same public link connections that make this new feature possible is what makes more advanced social graph analysis possible using tools like Mailana or Twiangulate. Those 3rd party services, while incredibly useful, will likely remain outside the realm of what Twitter would ever develop itself.

Photo from dacort on Twitpic.

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.

To achieve this, we must first stop arguing over the different flavors of search.

Because the promise of social network integration with search is a current favorite topic, we'll focus in this post on that: a class of social search. This is also a response to the ideas brought up by Alex Iskold in his post on the future of search.

Alex proposes that we rank search results by a kind of Social Relevancy Rank, first displaying results from friends and people whom we follow and later displaying results from "taste neighbors" and influencers, etc. FriendFeed already filters results by your friends' content first. Twitter's Trending Topics, by contrast, shows the crowd's perspective. While one's personal social circle could improve the relevance of some search results (and I noted some months back that this is a promising model), this type of filtering is more challenging than it sounds.

First, as Alex points out, "trusted opinions are scarce." Our friends couldn't possibly know everything we're interested in, and the smaller our social circle, the worse the problem becomes. Even with large social graphs, sooner or later we will undoubtedly search for a topic that hasn't been indexed in our friends' activity streams, and then we'll get few to no results and suffer an inferior user experience. We'd be better off turning to good ol' Google... the very thing we're trying to best!

Secondly, getting Social Relevancy Rank right involves a lot of insight into what users care about. Alex comments that, "This is not difficult for FriendFeed to do because... it knows who you care about." But does it? On FriendFeed, I follow only a limited number of the people I actually care about. Do those people alone account for the things I care about? And when I perform a search, does the engine know what I'm caring about at that moment? True, we have to start somewhere -- as PageRank did -- and tweak the algorithm over time. But suggesting that even a smart Social Relevancy Ranking is clued in to what we care about at any given moment is presumptuous at best given the state of the art.

Yet, having different levels of social relevance is a good theory, and Alex's demarcations are sound, in essence. But each level more likely indicates degrees of social proximity than relevance per se; although in some cases closer proximity may very well indicate greater relevance. The problem is that relevance is highly contextual. It depends on many factors, such as your profession, your search query, your friends, your friends' knowledge about those topics, and the information that is publicly recorded in their activity streams.

For example, a financial analyst (i.e. an expert) wouldn't care if her closest circle of friends was Twittering about how complicated a new tax code is. As an expert, she'd rather know exactly how the new policies affect an edge-case client of hers. Filtering search results by "friends and following" at one end and "the crowd in aggregate" at the other may fail equally in uncovering the right piece of information for her.

For general users, the "it depends" factor may be the urgency with which information is needed. When the need is urgent, people will actively search for the information (in any number of ways); other times, information may be welcome but only encountered serendipitously or consumed passively. Browsing feeds, Twitter posts, and Facebook streams are all passive ways of discovering information. Putting these activities on a continuum in which information search is active but information discovery is passive could look like this:

But to actually achieve a "Social Relevancy Rank," we have to consider how layers of social proximity map onto this search-discovery continuum.

When people actively look for a piece of information (e.g. the best Barbary Coast Trail guide for tomorrow's hike), they likely require trustworthy, high-quality information that could at least inform their decision. "Friends and following" could serve as a reliable social filter at this stage. But as the urgency subsides (e.g. just poking around for a mint julep recipe a week before a get-together), we relax our requirements and even welcome a wider set of results. At this stage, filtering results by friends of friends, influencers, experts, and even crowds in aggregate is appropriate.

Of course, serendipitously discovering information from "friends and following" would be welcome in other instances. So, to actually improve social relevancy in search engines and discovery services, there would have to be a distribution of acceptable social filters whose levels depend on how active the user is and what the user is searching for:

What this still fails to address, though, is how to assess the urgency of a user's needs or how to derive that level of urgency from the user's known behavior. This is a problem that engineers, designers, and HCI researchers have been struggling to solve for a long time (and a million dollars will get you only so far).

The problem of effective search runs deep. You can have all the flavors you want -- social, real-time, semantic -- and tomorrow's flavor will be merely another riff on the same tune. Yes, social networks and the social graph have the potential to meaningfully filter millions of otherwise undifferentiated pages of results. But words like "meaningful" and "relevance" are so contextualized -- varying as they do from user to user and usage case to usage case -- that they can't be expected to mean anything unless they are anchored by context. Mapping social proximity to users' active and passive information consumption could help us create more contextualized user experiences on the social Web, resulting in less time spent naming the latest flavor of search and more time spent actually improving search.

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.

Real-time Web search (of streams of activities) is a hot topic right now. Everyone, including Google and Microsoft, recognizes the value of using trusted contacts as filters. What was once called social search is now called real-time search, but this time it will really happen. First, it will be applied to streams and then to the Web in general.

What we are about to get is a Social Relevancy Rank. Whenever you search streams of activity, the results will be ordered not chronologically but by how relevant each is to you based on your social graph. That is, people who matter more to you will bubble up. How does this work? Well, there will be a formula, just as there is a formula for Page Rank.

Here is an idea so obvious that it is surprising Twitter has not implemented it already: front-load search results with people you follow. When you search for, say, "Wilco" on Twitter today, the results are in the chronological order. That is not really relevant because you do not know who most of these people are. But if instead you could see people you follow, the search results would be much more useful.

This is not possible on Twitter today, but it already works great on FriendFeed. There, results are filtered or ranked based your social graph. This is not difficult for FriendFeed to do because, on the one hand, it knows who you care about and, on the other, it applies its advanced feed search technology to your social graph:

This sounds awesome, but there is a problem. "Wilco" works well as a query because the band has just released a new album, but many other queries would return no results. Simply put, your friends on Facebook and people you follow on Twitter can't possibly have an opinion on every topic you may be interested in. This is a problem of sparse data: trusted opinions are scarce.

Small Worlds and Taste Neighbors

To solve the problem of sparse data, we need more data... obviously. One possible solution is to incorporate other sources that you trust (i.e. broaden your social graph). As a next step, search results could rank people you may not be directly following but who are being followed by people you follow. Or in Facebook-speak, friends of friends. You could argue that you are not familiar with their opinions and so cannot yet trust them, but given the small world phenomenon, their contributions are often just as valuable.

Another step could be to include people with similar tastes, so-called taste neighbors. This approach is common among vertical social networks such as Last.fm, Flixster, and Goodreads. These networks have ideas about which people, other than your friends, are like you. However, this is a costly calculation and takes time. In order for Twitter to do something like this, it would have to compare people based on links or perform semantic analyses of tweets over time. Yet even though this is a difficult problem, it will be solved in time.

The Influencers and the Crowd

Aside from using the "second degree" of your social graph or taste neighbors, a Social Relevancy Rank could front-load influencers. In the absence of any other metric, someone who is followed by hundreds of thousands of users is likely more relevant to you than someone you don't know at all. Using number of followers as a weight might be a good way to order the rest of the activity stream.

In general, combing through countless tweets from strangers is not terribly useful anyway. Just as people have stopped looking at anything beyond the first page of results on Google, sifting through pages of tweets in chronological order gets tedious quickly. What needs to be incorporated into the Social Relevancy Rank is the aggregate sentiment of the crowd: a score that tells you yay or nay and gives you an opportunity to drill into more results if you choose.

The Quest for the Perfect Filter

There is no such thing as a perfect formula. Even Page Rank isn't perfect. Yet we all use it and find it useful. Much as Page Rank has been adapted and tuned to search the web, Social Relevancy Rank will evolve over time to help us make sense of endless streams of activity. This ranking will have a profound impact on how we tap into our friends' opinions.

It will change the face of general Web searches in time, too. Today, results are automatically ranked by relevancy and freshness. Once Social Relevancy Rank is factored in, search results will be re-ordered based on social relevancy.

And now, as always, please tell us what you think? What would you expect from a search engine with Social Relevancy Rank built in?