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My Ten Favorite Tweets – Week Ending 020609

From the home office in Victoria, Australia…

#1: Interesting convo w/ colleague. Is there any risk to tweeting that you’re traveling on vacation? Burglars searching for such tweets?

#2: Guy was turned down for a job because he switched majors his freshman year of college. Say what? Details: http://bit.ly/23yHBT

#3: FriendFeed continues to roll out the powerful features. Latest? Much more granular search options, very helpful: http://bit.ly/VNYX

#4: I’m impressed w/ Yammer’s hustle. If you’re doing an internal preso on it, they’ll help you with the preso. Smart. E.g.: http://bit.ly/PR1A

#5: RT @beccayoungs I really do think the Amazon Kindle will be a game-changer. Check this out – Kindle to be a $1B product http://tr.im/eflz

#6: RT @barconati Oh no! Yahoo briefcase is closing. Believe it or not I still use it. More out of habit than anything else http://tr.im/e88z

#7: Mike Gotta on the rise of employee social profiles inside companies: http://bit.ly/135Vz Benefits and advice w/ nice Connectbeam shout-out

#8: Check out http://www.socialwhois.com/ Lets you search for people on based on keywords in their lifestreams. Very cool.

#9: RT @lehawes w00t! I made the Wall St. Journal today! Page A11 in print edition or online at http://bit.ly/iRcH

#10: After the WSJ coverage…@lehawes blogs about being included in a recent WSJ article: Taken Out of Context http://bit.ly/17aRy

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Google Alerts Ain’t Working – Why Don’t They Use Attention Signals?

Do you use Google Alerts?

I do. I’ve got seven of them set up. Generally, they’re pretty helpful. But they often suffer in terms of quality. Here’s a few comments with regard to that:

#1: @VMaryAbraham so am I. Google alerts and blog search have been delivering really bad quality results lately. Old and spam.

#2: Google Alerts actually sent me some useful info today instead of the usual mess of bizarre kitchen sink links from random years and places.

#3: @JesseStay my Google alerts are similarly getting less useful

One of my alerts is for ‘Enterprise 2.0′. I’m doing a pretty good job of staying on top of things in the Enterprise 2.0 Room on FriendFeed, but the Alerts are good back-up. And Google Alerts are the most common keyword notification service that people use.

So this is my question: what determines the links we see in those daily Google Alerts?

I ask this because of a recent experience with a well-received blog post that was not included in the ‘Enterprise 2.0′ Alerts. Compared to another post that did make it in to the Google Alerts, I find myself mystified as to what algorithm Google is using to generate its Alerts.

It’s not to say that Google Alerts don’t deliver some good posts – they do. But they seem to miss the mark pretty often as well, as the quotes at the start of this post show. I’ll relate my own experience below, based on objective factors, as opposed to my own declaration that “It was good post dammit!” ;-)

Tale of Two Blog Posts

I checked the Google Alert of January 18 for Enterprise 2.0. Here’s what I saw (my red highlight added):

google-alert-enterprise-20-011809

The highlighted post is a schedule of Web 2.0 sessions for Lotusphere 2009. If you’re into Lotus, good stuff. One session at Lotusphere was titled “INV101 -   From Web 2.0 to Enterprise 2.0: Collaboration, Productivity, and Adoption in the Enterprise”. Hence, its inclusion in the Enterprise 2.0 Google Alert.

I use that entry as a contrast to a post I wrote on the Connectbeam blog, titled Three Silos That Enterprise 2.0 Must Break. It’s a post that pushed some definitions of what a silo is and where knowledge management needs to move to. It was well-received, with a number of attention signals like Del.icio.us bookmarks and tweets.

And you’ll notice it’s not listed in the Alerts email above, or in any earlier ones. It was included in my ‘Connectbeam’ Google Alert. So I know Google had indexed it in its blog database. But it was not in the ‘Enterprise 2.0′ Google Alert. Which got me to wondering, what does it take for a post to make into the daily digest of Google Alerts?

I put together a comparison of the two posts: the Lotusphere post, and the Connectbeam Three Silos post. I wanted to see where the Connectbeam post falls short. Take a look:

google-alerts-tale-of-the-tape

The table above includes some typical Google attributes: PageRank, term frequency, links. It also includes the next generation of content ranking: comments, bookmarks, tweets and Google Reader shares. On either basis, it’s surprising that the Lotusphere post made the cut, while the Connectbeam post didn’t.

So I’m still trying to figure out what makes the difference here. Clearly, the Three Silos post struck a bit of a chord in the Enterprise 2.0 community. I know this not because of links by other bloggers (although they were there), but by the other Web 2.0 ways people communicate what’s of value to them.

How about it Google? Time to update your algorithms to include attention signals from our growing use of social media?

Social-Filtered Search

Recently, there was a lot of discussion about running searches on Twitter, using authority as a filter. The idea is to reduce Twitter search results to only those with a minimum number of followers. The idea garnered plenty of discussion. From that discussion, I saw some perspectives that I liked:

Frederic Lardinois: I would love to have the option to see results from my own friends (or those who I have communicated with through @replies) bubble up to the top.

Jeremiah Owyang: Organizing Twitter Search by Authority is the wrong attribute. Instead, focus search by your OWN social connections. People you actually know score higher relevancy. http://www.loiclemeur.com/engl…

Robert Scoble: On both services you should see a bias of tweets made by people you’re actually following. Who you are following is a LOT more important than who is following you.

Those ideas make sense to me, because they reflect the way we seek out information. I do think there’s room for search results beyond only your friends. Here’s what I mean:

social-filtered-search

The idea above can best be described as follows:

I’ll take any quality level of search results for my close connections, but want only the most useful content from distant connections.

The logic behind this is that any quality “deficiencies” in content generated by my close connections can be made up for by reaching and having a conversation with them. That’s not something I’d do with more distant connections.

The chart above has two axes: strength of ties and usefulness signals. Let’s run through those.

Strength of Ties

Harvard professor Andrew McAfee blogged about the strength of ties back in 2007. With an eye toward employees inside companies, he segmented our connections as follows:

strong-weak-potential-ties-mcafee

The segmentation works inside companies, and it also applies in the personal world. For example, on FriendFeed, my Favorites List is akin to Strong Ties. The rest of the hundreds of people I follow are my Weak Ties. Friend-of-a-Friend entries I see are my Potential Ties. And of course there are a lot of people I never see. Those would be the “None” Ties.

The hardest part of this segmentation is that people aren’t likely to take the time to create and update their Strong Ties. Rather, Strong Ties should be tracked via implicit signals. Whose content do you click/rate/comment on/bookmark/share/etc.? Extend this out to email – who do you correspond with the most?

For example, I tried out the social search of Delver. It lets you load in your social networks, from places such as Facebook and FriendFeed, and uses content from those connections as your search index. Innovative idea. What happened though is that when I run a search, I get a deluge of content. My social networks are too big to make the service really useful.

Here’s where apps that handle a large percentage of my clicks and interactions will have an advantage. FriendFeed, with an extensive library of content from my connections, has this quality. Inside the enterprise, workers interact with a limited set of applications. The company’s IT department can set up tracking of interactions to identify implicit Strong Ties.

Bottom line: determining Strong Ties via implicit interactions is scalable and useful.

Signals of Usefulness

I’ve already described these in the paragraphs above:

  • Clicks
  • Ratings
  • Comments
  • Bookmarking
  • Sharing

Implicit data + explicit signals are the most powerful indication of usefulness.

Putting These into Place for Social-Filtered Search

When I say that I’d want to receive search results, even without many signals of usefulness, from my Strong Ties, here’s an example.

  1. I’m planning to run a marathon
  2. What marathon training plan should I use?
  3. I run a search for marathon training.
  4. I see a tweet from one of my Strong Ties: “Just started my marathon training this weekend. 4 miles FTW!”
  5. I @reply my Strong Tie, ask what training program he’s using.
  6. I now can leverage someone else’s work on this subject.

Of course, I’d want to see well-rated marathon training programs too, like Pete Pfitzinger’s Advanced Marathoning. I’d want to see the content from my distant/non-existent connections that had the highest signals of usefulness. Not unlike Google’s algorithm.

But the key here is that I’ll make up for any deficiencies in the utility of content for someone I’m close to by contacting them. A search on ‘marathon training‘ in Twitter shows a lot of results. But I’m not going to reach out to most of these folks, because I don’t know them. I only want those with whom I can have a conversation.

As I said, the ability to track both implicit and explicit activity is key to making this work. Facebook, FriendFeed, Twitter and Enterprise 2.0 all seem like good candidates for this type of search.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Social-Filtered+Search%22&who=everyone

My Ten Favorite Tweets – Week Ending 121908

From the home office in Short Pump, VA…

#1: “Each year there is more information created on the Web than in all the previous years combined. ” Jim Breyer of Accel http://bit.ly/12nH3

#2: Per a Yahoo product rep, the average search session lasts 15 minutes http://bit.ly/eSrr

#3: What a lovely bitchmeme we have this weekend…and in case you’re curious, here’s Dave Winer’s definition of a bitchmeme: http://bit.ly/MYJm

#4: It takes 6-9 months for a blog to get fully ramped up in terms of readership per @duncanriley http://bit.ly/W0LO

#5: Great story of a Best Buy meeting where a raging Twitter conversation happened while the room was respectfully quiet http://bit.ly/FkKM

#6: 60% of e2.0 vendors will be bought or go under in 2009, according to Gartner http://bit.ly/Acyg >> Oy!

#7: Today is my one-year anniversary of Twitter. First tweet? “Trying to get warm-n-fuzzy about Twitter…” http://bit.ly/fss2 Accomplished!

#8: Office 2007 – really, really confusing if you’re used to Office 2003 or prior versions.

#9: FriendFeed got a spammer attack, the team quickly took care of it. One thing I wonder: why do these spammers always have such bad grammar?

#10: My sister just earned her PhD in linguistics this morning from Georgetown. Way to go Helen!

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22My+Ten+Favorite+Tweets+-+Week+Ending+121908%22&who=everyone

Supply-Demand Curves for Attention

The basic ideas behind the Attention Economy are simple. Such an economy facilitates a marketplace where consumers agree to receives services in exchange for their attention.

Alex Iskold, ReadWriteWeb, The Attention Economy: An Overview

The attention economy. It’s a natural evolution of our ever-growing thirst for information, and the easier means to create it. It’s everywhere, and it’s not going anywhere. The democratization of content production, the endless array of choices for consumption.

In Alex’s post, he listed four attention services, as they relate to e-commerce: alerts, news, search, shopping.  In the world of information, I focus on three use cases for the consumption of information:

  1. Search = you have a specific need now
  2. Serendipity = you happen across useful information
  3. Notifications = you’re tracking specific areas of interest

I’ve previously talked about these three use cases. In a post over on the Connectbeam blog, I wrote a longer post about the supply demand curves for content in the Attention Economy. What are the different ways to increase share of mind for workers’ contributions, in the context of those three consumption use cases.

The chart below is from that post. It charts the content demand curves for search, serendipity and notifications.

micro-economies-of-attention-3-demand-curves-for-content

Following the blue dotted line…

  • For a given quantity of user generated content, people are willing to invest more attention on Search than on Notifications or Serendipity
  • For a given “price” of attention, people will consume more content via Search than for Notifications or Serendipity

Search has always been a primary use case. Google leveraged the power of that attention to dominate online ads.

Serendipity is relatively new entry in the world of consumption. Putting content in front of someone, content that they had not expressed any prior interest in. A lot of the e-commerce recommendation systems are built on this premise, such as Amazon.com’s recommendations. And companies like Aggregate Knowledge put related content in front of readers of media websites.

Notifications are content you have expressed a prior interest in, but don’t have an acute, immediate need for like you do with Search. I use the Enterprise 2.0 Room on FriendFeed for this purpose.

The demand curves above have two important qualities that differentiate them:

  • Where they fall in relation to each other on the X and Y axes
  • Their curves

As you can see with how I’ve drawn them, Search and Notifications are still the best way to command someone’s attention. Search = relevance + need. Notifications = relevance.

Serendipity commands less attention, but it can have the property of not requiring opt-in by a user. Which means you can put a lot of content in front of users, and some percentage of it will be useful. The risk is that a site overdoes it, and dumps too much Serendipitous-type content in front of users. That’s a good way to drive them away because they have to put too much attention on what they’re seeing. Hence the Serendipity curve. If you demand too much attention, you will greatly reduce the amount of content consumed. Aggregate Knowledge typically puts a limited number of recommendations in front of readers.

On the Connectbeam blog post, I connect these subjects to employee adoption of social software. Check it out if that’s an area of interest for you.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Supply-Demand+Curves+for+Attention%22&who=everyone

Hey Yahoo! Forget MSFT, GOOG. Change the Search Rules.

These I wish I knew the moment I was turned off on Yahoo and what the root cause may be, but I no longer use anything Yahoo (except my Flickr account if you want to count that).

Vince DeGeorge, on FriendFeed

I was doing the same thing until I started using delicious as a search tool. Finally realized how powerful it was, and have been using it since.

Shaun McLane, on FriendFeed

I have previously written that Delicious search is one of the best ways of searching for things when a standard search doesn’t pull up what you are looking for. After Google, it is my favorite “search engine.”

Michael Arrington, TechCrunch, Delicious Integrated Into Yahoo Search Results

The latest news is that Microsoft is reaching out to Yahoo again. In fact, a couple reports (here, here) say that Microsoft wants to buy Yahoo’s search business.

Before any such transaction occurs, it seems worthwhile to think about what Yahoo could do with its existing assets. The three comments above are insightful. Yahoo is slowly losing share of mind, although it’s existing base of users will be around for a while. At the same time, there are nuggets in the Yahoo empire.

Search via del.icio.us ranks as one of those nuggets. Another nugget? Yahoo! Buzz. According to ReadWriteWeb, Yahoo! Buzz has surpassed Digg in terms of traffic, and its demographics better reflect web users.

Yet, Yahoo struggles against Google in the highly lucrative search market. Google increased to 67.9% of searches in April 2008, compared to Yahoo’s decline to 20.3% of searches.

What should Yahoo do? Stop playing Google’s game. Rewrite the search rules by embracing the social web fully, leveraging the social media assets it has.

And in doing so, demonstrate an aggressive path to make Yahoo a social media titan.

A Proposal for “Socializing” Yahoo Search

In January 2008, TechCrunch ran a post with a preview of del.icio.us integrated with regular Yahoo search results. Included in the search result links would be stats that tell a user:

  • Number of del.icio.us users who bookmarked the page
  • The top tags they used on the page

Both of those stats appear to be clickable. By clicking on the number of users stat, I assume a user would be taken to the del.icio.us page showing the users who bookmarked the page. If one clicked a tag, you’d land on the del.icio.us page for all web pages with that tag.

That’s a good start. But Yahoo can do better. Below is a diagram that shows how Yahoo can use its existing assets, combined with a good dose of the new social media experience, to radically change search:

Here’s a breakdown of what’s going on with the proposal.

Search Rankings

From what I’ve read, Yahoo has pretty much caught up to Google in terms of search performance. That means the use of links and clicks to rank websites is pretty common across the two search engines. However, Google does have the advantage of three times the traffic, which makes its insight into what’s relevant better than Yahoo.

But Yahoo has its own in-house advantages: del.icio.us and Yahoo! Buzz. Both address shortcomings in the links and clicks rankings for search engines:

  • Links require a media site or blogger to take the time to link. These links are insightful, but lack the broader reach of what Web users find relevant.
  • Clicks occur before a searcher knows whether the landing site is valuable. They don’t describe its usefulness after someone has clicked onto the site.

With del.icio.us and Yahoo! Buzz, Yahoo can tap into users sentiments about websites in a way that Google cannot. These insights can be used to influence the ranking of search results.

Search Results – Your Friends or Everyone

Here’s where it can really interesting. Notice I keep the general search results outside the influence of what your friends think. I think that’s important. A person should see results outside their own social circle. Otherwise, it will be hard to find new content.

But there is real power in seeing what your friends find valuable (e.g. see FriendFeed). So Yahoo should let you easily subscribe to other people for content discovery. Yahoo already has a head start on letting you set up your subscriptions:

  • Yahoo Mail
  • Yahoo Instant Messenger

In addition to that, you should be able to easily subscribe to anyone who publicly shares content they find interesting. Both del.icio.us and Yahoo! Buzz have public-facing lists for every user of what they bookmark or ‘buzz’. After viewing those lists, I should be able to easily subscribe to these users.

Once your network is developed, it becomes a powerful basis for improving information discovery.

Search Results – Associated Tags

Whenever tags are available from del.icio.us, they should be visible for each web site shown in the search results. This is what TechCrunch previewed. What do tags tell a user?

  • A way to discover other sites that might be relevant
  • Context for the web site
  • That someone thought enough of the web page to actually tag it

Tags should come in two flavors: everyone and your network. Clicking on a tag should display the top 10 associated sites right on the search results page. For more sites associated to the tag, the user is taken to del.icio.us.

Keeping the top sites on the search results page is important to make people use the functionality. Leaving the search results page just to see the sites associated to a tag will cause adoption to drop signficantly.

Search Results – Associated People

Each web page in the search results will show the number of people who have (i) bookmarked the site; or (ii) Yahoo! Buzzed the site. These numbers give a direct indication of how many people, not websites, found the web page valuable.

Clicking these numbers displays a list of the people, along with their most recent activity. This gives users a sense of whether they want to subscribe to a given user or not.

Search Agent

Once users perform a search, they will be able to subscribe to new content matching their search results. These subscriptions can be based on different criteria:

  • Any new content matching the search term (Google does this via Google Alerts) or a tag
  • Any new content matching the search term/tag and bookmarked by someone to whom the user subscribes
  • Any new content matching the search term/tag and Yahoo! Buzzed by someone to whom the user subscribes
  • Any new bookmarks or Yahoo! Buzzes by someone to whom the user subscribes

New content notifications occur via email or RSS. RSS can be anywhere, including on the user’s My Yahoo page. Again, FriendFeed has shown the power of these content streams.

Final Thoughts

My little post here isn’t the only idea someone could float. But it does at least address taking Yahoo much more deeply into the social media world, where users drive the value.

Yahoo revealed details of a proposed del.icio.us integration back in mid-January. And then nothing. Yahoo previewed Yahoo Mash, a new social network in September 2007. And then…nothing. The last post on the Yahoo Mash blog was January 11, 2008.

Yahoo has so many amazing assets. Search, email, portal home page. Several beloved social media apps (Flickr, del.icio.us, Upcoming). Yet they have not put them together into a cohesive strategy and experience.

And now, talk of selling the search business? C’mon Yahoo. You’ve got too much going on to give up yet. Stop playing by others’ rules. Make your own rules with the amazing assets you have.

*****

See this item on FriendFeed: http://friendfeed.com/e/1b07226a-b51b-f386-fbb8-bdaece83e9fe

Did You Notice a Change in Your Google PageRank?

Something changed the past few days in the Google PageRank of this blog. Posts that were getting a predictable average number of hits each weekday are suddenly zooming up in terms of views. I don’t know what my PageRank was before (being a blogger n00bie and all), but it’s a 5 now. Perhaps a new round of the Google dance?

I’m not alone in seeing this. Here are a few others who have noticed the change recently:

Frederic of the Last Podcast tweeted:

just noticed that my pagerank must have increased from 4 to 5 in the last few days – nice :)

Mark O’Neill of Better Than Therapy wrote:

I got a pleasant surprise today when I noticed that my Google pagerank has been increased by one. I am now a 6 which is nice.

And on Search Engine Land, Barry Schwartz noted:

Over the past few days, many webmasters and SEOs have been noticing an update to the PageRank score found in the Google Toolbar. Usually PageRank updates aren’t that noteworthy, but it seems something is different about this PageRank update.

I’m no expert on search engine optimization, but it is interesting to hear Barry say that something is different about this PageRank update. Click here for a post on Court’s Internet Marketing School discussing the PageRank changes, along with a ton of reader comments.

One Example: Farewell Email Post

I have a post on this blog that’s been up for nearly two months now. How to Write a Farewell Email to Your Co-Workers provides a humorous look at that ritual of leaving companies, the farewell email. Given that people tend to leave on Fridays, the page views of this post follow a predictable path, increasing each day to a weekly high on Friday.

This Wednesday’s views were the highest ever for a single day, and we’re not even at Friday yet. The chart below shows the daily views for the post, with the Wednesdays highlighted by arrows.

I normally wouldn’t note the increase in views, as it risks coming across as some sort of bragging. But the magnitude of the change is pretty significant. And here’s why it’s happening. The post has now risen to the #2 position in a Google search on ‘farewell email’. It wasn’t that way before. I’d check on how the post ranked periodically, and it tended to be around the 10th or 12th result. So a jump of 8 or 10 places in search results is worth 3 times the hits. Now I see the SEO industry in a whole new light!

Of course, this blog isn’t about ad revenue. And the blog’s heavy Web 2.0 content may not appeal to the search engine visitors. But, I decided to add a message for my farewell email visitors:

Welcome to the blog. I know you’re here for tips on writing farewell emails. If you’re at all interested in Web 2.0, I invite you to look around the blog a bit. Use the tag cloud below, or the recent posts on the left-hand side to find info. Also, let’s connect on Twitter and FriendFeed: twitter.com/bhc
friendfeed.com/bhc3

From an advertising perspective, there’s a mismatch between the farewell email post and most of the blog’s other content. So I’m not ‘targeting’ the right audience. But if any of those visitors decide to stick around, I hope they get enjoy the blog.

*****

See this item on FriendFeed: http://friendfeed.com/e/a8133912-d2e9-f680-6592-a66e08abb717

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