Slides from the Social Graph Symposium panel

Some introductory slides from a panel session at the Social Graph Symposium.

Social Graph Symposium Panel – May 2010 – Presentation Transcript

1. Social Graph Symposium Panel
Ho John Lee | Principal Program Manager | Bing Social Search
2. About me:
Ho John Lee
hojohn . lee @ microsoft . com
Past: Bing Twitter (v1), SocialQuant, trading, investing/consulting (China, India)
HP Labs, MIT, Stanford, Harvard
Current: Bing Social Search – graph and time series analysis, data mining
Twitter, Facebook, new products, technical planning
3. What can we do by observing social networks?
On the internet, no one knows you’re a dog.
But in social networks, we can tell if you act like a dog, what groups you belong to, and some of your interests
4. How many Twitter users are there?
from a search on twopular, May 2009
5. Graph analysis for relevance and ranking
Spam marketing campaign
(teeth whitening)
Naturally connected community (#smx)
Real time relevance needs data mining to filter and rank based on history
Spammy communities can be highly visible
Social graph, topic/concept graph, and behavior/gesture graphs are all useful tools
6. Information diffusion in the graph
Observed incidence network of retweets in Twitter
Kwak, Lee, et al, What is Twitter, a Social Network or a News Media? WWW2010
Information flow and behaviors form an implicit interaction graph
7. Topic / sentiment range, volume, trend analysis
What is the baseline rate of mentions / sentiment per unit time?
Look for changes in attention flow around a subject, location, topic
Watch for correlated signals from multiple sources
Consider source relevance and authority as well
8. Applying graph analysis
Attention flow vs information flow
Leads to utility functions, cost functions
Variable diffusion rates by actor / network / info type
Predicting interests and affiliations
Content creation follows attention
Self-organized communities of attention
If there’s no content, you can ask for some
Observable propagation of information
9. Clustering and fuzzing properties and identities
* Frequently used terms can identify interests, affinities, latent query intent
* But can potentially be used to identify likely individual users!
* Infochaff – fuzzing out identity, behavior, properties
10. Thank You
Ho John Lee
hojohn . lee @ microsoft . com

RESEARCH: Insights from the latest social graph studies
Moderator: Eric Siegel – President at Prediction Impact and Conference Chair at Predictive Analytics World
Sharad Goel – Research Scientist at Yahoo
Ho John Lee – Principal Program Manager at Microsoft
DJ Patil – Chief Scientist at LinkedIn
Marc Smith – Chief Social Scientist at Connected Action Consulting Group

My slides from the Real Time Search Panel at SES Chicago last week

Although real time search is fairly new, as we end 2009, the ability to index and search fresh results is rapidly becoming a commodity, with Bing, various startups, and now Google all integrating status feeds from social networking services. The next set of challenges in 2010 will be around providing better relevance, information discovery, and topic exploration for social search, using signals from the dynamic behavior of users and their interaction with the social and topic graphs.

I gave a short talk on real time and social search for a panel at SES Chicago last week. I’ve been heads down for the past few months working on Bing Twitter Search, so now that the first launch is out the door it was a nice chance to talk with people about some of the work we’re doing. There was a lot of interest in the sentiment, trend, and social graph analysis slides (9 and 10). I will write about those in a separate post, but wanted to get the presentation up for those who have been asking about it.

What’s Different about Real Time and Social Search – HJL Slides For SES Chicago Dec 09

View more presentations from Ho John Lee.

What’s Different about Real Time and Social Search – HJL Slides For SES Chicago Dec 09 – Presentation Transcript

  1. What’s different about real time and social search?
    Ho John Lee
    Principal Program Manager
    Bing Social Search
    Search Engine Strategies
    Chicago – December 7, 2009
  2. What’s Real Time Search Good For, Anyway?
  3. Twitter is Great for Watching Uninformed Panics Unfold Live
    …or finding balloons
  4. Some characteristics of Twitter / Social media
    Immediacy, Sentiment, Brevity
    Not always accurate
    Feelings, reactions, impressions
    Context is often essential to determine meaning
    Gestural – @user, #hashtag, RT, favorites, follows
    Self-organizing communities of attention and authority
    Content follows attention
    People talk about what others are talking about
    Observations and commentary from everywhere
    If there’s no content, you can ask for some
    Extreme head and tail coverage
    Low relevance “noise” can become “signal” in aggregate
  5. Your product or brand could suddenly be at the center of a huge conversation
    Tiger Woods
    Balloon Boy
    Breaking Story
    Persistent Story
    Big Story
    Bigger Story
  6. Some characteristics of Real time / Social Search
    • Real time and social search is qualitatively different from traditional web search
    • Differences in ranking, relevance, use model
    • Social graph, user behavior, location, event correlation and other input signals
    • Real time search is frequently about discovery, not search per se
    • “what is everyone talking about”, followed by “what are people saying about ”
    • Top real time and social search results will usually differ from top web search results
  7. Bing Twitter Search at a glance
    Top Tweets
    Top Shared Links
    Tweets/Sentiment per link
    Adult /Spam filter; Tweets/Links ranking & relevance
  8. Bing Fall 2009: Twitter vertical, News, MSN, Maps
    MSN Local Edition
    Page 2: Tweets or Links
    Page 1: Tweets & Links
    Twitter Answer on News SERP
    MSN Hot Topics
  9. Topic / sentiment range, volume, trend analysis
    What is the baseline rate of mentions / sentiment per unit time?
    Changes in attention flow around a subject, location, topic
    Watch for correlated signals from multiple sources
    Consider source relevance and authority as well
  10. Graph analysis for relevance and ranking
    Spam marketing campaign
    Naturally connected community
    Spammy communities are highly visible – don’t be part of one!
  11. Bing Twitter Maps Demo
  12. To rise above the noise, there is more to do as search gets more social
  13. Thank You
    Ho John Lee
    hojohn . lee @
The session was moderated by Barbara Coll, CEO, Inc., with panelists Bill Fischer, Co-Founder & Director, Workdigital, Ltd., Rob Walk, Managing Partner, NovaRising, Nathan Stoll, Co-Founder, Aardvark, and  Ho John Lee, Principal Program Manager, Social and Real Time Search, Microsoft Bing.

A last look at Twitter userbase growth (through June 2009)

A number of people have been asking about updates to the earlier posts on Twitter’s user profile population as well as some statistical analysis.  I’m joining the Microsoft Bing search team so I probably won’t be sharing as much data in the future, but I wanted to get a couple of charts out first.

Here’s an updated look at Twitter’s user base growth, through June 2009. This survey has many spam accounts pruned out, so the actual number of user profiles at any point in time is probably higher than the graph plotted here. Up and to the right, heading past 13M is the main takeaway. Also note that the majority of Twitter profiles have been created within the past few months. Compare with the graph through May 2009


Here’s the corresponding estimate of new user accounts per day. That first big spike is the Oprah show featuring Twitter.  Not sure exactly which media events go with the more recent spike, likely some combination of Ashton Kutcher vs CNN and other celebrities on a campaign to get more followers.  As a reminder, the graphs don’t really drop off at the  right edge, that’s just from new users not being discovered immediately.


Unfortunately I probably won’t be putting together any stats visualizations here as I transition the SocialQuant work to Microsoft Bing. But  I’m looking forward to help bring some interesting applications for Twitter and other social media on the Bing platform, and hope you’ll be able to enjoy some results there in the near future.

When you come to a fork in the road…

Crossroads of the World at the Beach Bar, Waikiki

Crossroads of the World at the Beach Bar, Waikiki

As some of you know, I have been exploring a variety of paths forward for SocialQuant, my real time social search and analytics project. My family, friends, and colleagues have given me much support, patience, and advice during this process, which has reached a crossroads, and as Yogi Berra says, “When you come to a fork in the road, take it!”

The rise of Twitter, Facebook, and other social media, combined with web-based applications, smartphones, and cloud computing have all set the stage for new applications and use models based on social discovery, collaboration, and communications, in addition to traditional search. What we’re all calling “real time search” lately isn’t exactly real time, nor is it exactly search, in which you find a definitive/authoritative answer. Much of the opportunity revolves around discovering people, discussions, and events that are relevant to you and bringing it to your attention in a timely, actionable fashion. Information streams from social media are transient, unreliable, and noisy. At the same time, the sheer volume of data can help provide the basis for building better filters. As an added bonus, you can ask questions to people in the social graph itself, and there are numerous examples of communities of interest forming around current events such as Barack Obama’s inauguration, the Iran elections, or even Michael Jackson’s funeral, all of which help surface information content, opinion, and sentiment that were previously inaccessible online. One interesting aspect of real time social media is that it’s not just algorithmic, it’s based on human connections and emotions. So a message  that “feels right” from people you trust can be more relevant than one that is “correct” at times.

The challenge then is in filtering and ranking the massive flow of information in a way that helps direct the user’s limited (and non-expanding) time and attention in a way that’s most valuable to them. With today’s information technology, amazing things are possible with limited resources. I personally have more computing and storage resources than the facility we launched HP’s original photo site with (for millions of dollars), at a fraction of the cost, routinely pushing around datasets of millions of rows on the local development servers. Unfortunately, that’s just the ante to get started on the problem. Running ranking, clustering, and semantic analysis for filtering the ever-growing stream of social media eventually requires web scale computing, even with careful problem selection and data pruning. The bar is also going up every day as the social media user base grows, and as well funded teams make progress on their platforms (+Google).  So very shortly, to be competitive in real time, social search and discovery is going to require access to lots of data and either getting a datacenter or working with someone who has one.

In my case, I have recently chosen the latter path, and will be joining the Microsoft Bing search team, focusing on real time and social search. Microsoft itself has been showing signs of a renaissance, with search relaunching, Windows 7 looking leaner, Azure becoming non-vaporous, more web APIs getting published, core online applications starting to turn up, and a cool Office 2010 video. Even Mini-Microsoft is getting positive recently. And Google is starting to have “bigness” issues.

I look forward to working with Sean Suchter and the Microsoft Bing search team (and likely expanding their carbon footprint) in pursuit of new applications and services as the social media and online application space evolves.

You can follow along on Twitter (@hjl). As always, any and all opinions here are solely mine and do not reflect the position of any past, present, or future employer, partner, or business associate.

Follow suggested users, attract instant spamcloud

Despite Twitter’s amazing growth rate, there is general agreement that the Suggested Users List and the new user experience has shortcomings. As an experiment, I created a new Twitter account. I wanted to see what the experience might look like for someone interested in, but otherwise completely unfamiliar with the service. During the signup process, it automatically picks some suggested users (apparently random), which I selected all of, about a dozen or so. Then it asked for my email credentials to check for other people I know on Twitter, which I declined, since I generally don’t give web applications access to my email services. Then I went back to “Suggested Users” under the “Find People” section, and selected all of them. In total, the Suggested Users list got me up to 237 friends in my incoming stream.

Within a few minutes of completing this process, I already had 13 spam followers offering affiliate links for cameras, porn, and twitter followers. A day later I was up to 41 spam followers, plus 4 follow-backs from accounts I followed in addition to the Suggested Users List.

twitter-newuser-spam-090705There are two different issues here: 1) finding a set of interesting / relevant people for new users to follow, and 2) limiting the impact of spam and affiliate marketers, who appear to be scanning the follower lists of the Suggested Users to identify new accounts to spam.

Twitter’s user growth per day

Twitter estimated new users per day through May 2009

Twitter estimated new users per day through May 2009

Here is a companion to the Twitter user population growth chart from last week. This chart shows an estimate of the number of new users per day. The dashed blue bar is the 2009 US inauguration of Barack Obama, and the extreme spike is the Oprah Winfrey show featuring Twitter.

The data used for this chart isn’t as complete for the last week or so at the right hand edge, i.e. the rate of new user signups hasn’t gone to zero, and in fact remains quite high, not 100k users per day, but well above the “pre-mainstream adoption” user signup rates, in the range of 30-50K users/day. As of mid June, Twitter has more than 8M user accounts that have been created.

Twitter’s amazing user growth

Twitter estimated userbase through May 2009

Twitter estimated userbase through May 2009

The graph above shows an estimate of Twitter’s user population from its launch in March 2006 through May 2009, based on a sample of around 6 million observed user profiles. The dashed blue line is around the 2009 US inauguration of Barack Obama and where the transition from early adopter to early mass audience seems to have taken off.

The entire user population of Twitter appears to have reached 1 million sometime in January but today there are several accounts that have over 1M followers each.

Stated another way, if you signed up before February 2009, you can consider yourself something of an early adopter on Twitter, and among the earliest 15% or so of the entire user population.

The numbers in this survey are inexact but representative, taken from research I’ve been doing for SocialQuant and FailWatch.  There is some survivor bias built in, since I’m pruning spam and suspended accounts. Only Twitter knows the true state of the user base and the social graph, of course.

The initial Twitter users tend to know each other more in real  life, since much of the social network grew from friends of founders, SWSX attendees, and the San Francisco / Silicon Valley tech community. The more recent (post-Obama)  arrivals tend not to have connections to those networks, and often don’t know anyone else to follow. They arrive via mass media and celebrity campaigns, and end up following mass media and celebrities, either from the suggested users list or because those are the only people they know of.

If you look carefully, you can see the rate of increase slows down toward the end of the graph. There was a huge ramp in  new user signups around the time of the Oprah show, which has receded somewhat. This has led to blog posts about Twitter’s impending demise, but looking back, there have been previous surges in the user base (typically around SXSW etc) which led to a peak, then a drop in new user signups to an off-peak but higher-than-before average. So far the current surge is the largest, but seems to be following the pattern. In the absence of any  new driver, user growth should continue at an off-peak but higher level, until the next big jump, or something better comes along.

Genius, in search of lab coat


Didn’t attend ETech this week, but thanks to a Twitter pointer from Gene Becker,  I did take a few breaks to participate in a collaborative future forecasting experiment at the event, organized by Institute For the Future / Signtific Labs. The general idea is to enlist game players to offer Twitter-like short notes with outlier ideas regarding a scenario under discussion, in this case the consequences of inexpensive ($100) 1kg microsatellites (“CubeSats”) capable of high speed networking and remote sensing. The same game framework could be used for any scenario, though. Bonus points are awarded to “Super-Interesting” ideas and ideas that result in additional discussion, which helped me out on the scoreboard.

Gene (“ubik“) won a “Feynman” award on the first day, and I managed to end up with a high score at ETech, thus winning a lab coat to go with my “Genius” label.

Some of my favorite future forecast contributions from “What will you do when space is as cheap and accessible as the Web is today?” (slide summary here):

Jurisdiction-free data haven built with csats full of rad-hard flash memory, hbase-style distributed replication across multiple nodes. Subpoena-proof anonymizers, for better or worse. Alternative, universal internet currency evolves, outside any government’s central bank control. Following forced disclosure of banking client list, Swiss government recognizes anonymous cSat net IDs, followed by Cayman, Bermuda etc.

CSats deorbited in vacant areas of oceans as impulse input to passive sonar imaging. Oceanographers get great maps, submarines lose stealth. Depending on how accurately you can drop a CSat, you can effectively “ping” a region and listen to the return signal through existing arrays. This really messes with strategic deterrence since now subs are vulnerable to first strike. But CSat deorbit is cheap WMD for all. On the positive side, detailed acoustic propagation data leads to new insights on ocean dynamics – bathymetrics, thermoclines, currents, etc. A similar version of dropping CSats on land might yield useful seismic imaging. But these would all be surface impulse, not at depth.

Csat data networks circumvent the Great Firewall of China and other govt access controls, leading to broader/safer citizen engagement online

CSat operating interface is marketed as a toy, like Tamagochi. Recharge, collect interesting data, avoid mean csats, team with friends. Organizations might post cash prize/rewards for things like locating missing ships, oil/trash dumping at sea, smokestack emissions, etc

Commodity traders are early adopters of CSat operator networks. Looking for crop yield data, mine production volumes, freight shipments etc. Among other things, CSat observations could give a more accurate estimate of “floating” oil parked in tankers as well as ongoing demand. Similarly, you’d get a decent idea of iron ore production by watching BHP’s railway in Australia, and the demand side in China, Korea etc. CSat data could improve the market visbility into supply/demand. But one might start creating Potemkin mining/farming operations etc… Sadly, credit derivative risk is not observable via CSat.

Ubiquitous, near real time satellite surveillance. No more privacy outdoors. But really good Google Maps. Ultra high resolution terrain maps of the world synthesized from multiple satellite passes/viewing aspects. Long term studies of effects of erosion, farming, development, earthquakes, flooding, drought, etc. Insurgents, militias, and terrorists get real time tactical data feeds, make use of homebrew UAVs, sensors, and in-field dispatch from afar. Turf wars among poppy and marijuana growers who now know where each other’s fields are. All vehicles – car, truck, rail, container, airplanes, etc – get a sky-facing ID plate. Maybe these should just be really big QR codes with an authoritative registry to foil car thieves from painting on bogus “plates”.

Now I need to figure out how to collect that lab coat.

Why I’m not connected to you on Facebook or LinkedIn (but do follow on Twitter and Friendfeed)


Here are my current informal policies for using Facebook, LinkedIn, Twitter, and Friendfeed.  Short version – Facebook and LinkedIn I use for people I know personally, Twitter and Friendfeed any interesting input is welcome.

Facebook: This has been rapidly going mainstream lately. I had a mostly unused account for a long time, which has become more interesting/active as people I know sign up.  I presently only link to people I know in real life. Facebook is interesting because there are people I haven’t interacted with for years (high school friends etc) as well as people that live next door (literally) and colleagues from past work projects all mixed together, and they all get to eavesdrop and engage in casual/passive interaction. I currently have my Twitter feed linked to update my Facebook status, which means my messages are probably cryptic to about half the readers at any given time.

LinkedIn: I originally only linked to people I worked with and knew very well. I have broadened out the criteria over the years, and at this point I will link to people that I haven’t worked with but have at least actually met and had a conversation with. I basically don’t link to people I don’t know and haven’t met, though. I’d to at least be able to recognize people I’m linked to, and have a clue about what they’re like. So no “LinkedIn Open Networking” for me.

Twitter: I look for interesting (to me) streams, whether or not I know the author. Most of my twitter feed is people I haven’t met in person.  I follow people I know in real life, and also discover people who have commented on something that turned up in a conversation or a search. I don’t auto follow, although I do try to take a look at who’s on my follower list periodically to see if there is someone I should add.  Twitter has also been the most interesting for making new connections with people in real life, as you can get a sense of topic people are thinking about and what they’re more generally like.  I use Twitter for scanning a range of topics, so I’m a little less interested in people with huge follower counts and more interested in people kicking out uncorrelated but interesting ideas and data.  I’m working on tools for scanning and filtering status and sentiment streams, so in theory a bigger source network is better, if you can make effective use of it.

Friendfeed: Sometimes I feel like Friendfeed is the Robert Scoble/Louis Gray channel, but I have seeded it with my Twitter feed and have gradually added people as they are exposed through the “friend of” feature.  I always have the feeling that I’m not making the best use of Friendfeed. I like the conversations that pop up on posted items, but wish for the range of input that comes from the huge user bases on Twitter and Facebook. Then again, maybe not Facebook inputs here, I also enjoy the relative skew towards content from early adopters that persists for now on Friendfeed.

If I know you in real life, feel free to send me a Facebook or LinkedIn request, there have been a lot of people signing up lately and I’ve been enjoying reconnecting with people I haven’t heard from in a while.  If I don’t know you (yet), you’re welcome to follow on Twitter (@hjl) or Friendfeed (hjl).

Registered for SF MusicTech 2009

Took advantage of the discounted ($49 through end February) early registration for SF MusicTech, coming up on May 18th.

The SanFran MusicTech Summit will bring together the best and brightest developers in the Music/Technology Space, along with the musicians, entrepreneurial business people, press, investors, service providers, and organizations who work with them at the convergence of culture and commerce. We will meet to discuss the evolving music/business/technology ecosystem in a proactive, conducive to dealmaking environment.

Unfortunately, it overlaps with ICWSM09, will try to make both though.

Link posts seem to be working again

The automatic nightly link posts from stopped working properly sometime last year. The links would get posted, but had extra “\n” inserted at every line break. Here’s an example. An unexpected side effect of having “ugly” link posts is that I mostly stopped posting links to for a while.

As part of the recent blog platform update, I’ve switched from the “experimental” nightly blog posting to Postalicious, which seems to be working nicely, you can see the new link post style (and the old ones too, unless I get around to cleaning them up) here.

New and improved

This evening I’m rolling out a long overdue update to the blogging platform. It’s been a little complicated, because I ‘ve been running a heavily customized WordPress 1.5.2 for a long time, and there have been a lot of changes since then to WordPress, various plugins, and the underlying database (the current release is 2.7.1).

hjl-weblog-feb09-before hjl-weblog-feb09-after

The new version is based on Atahualpa, which has many customizable options. The Recent Posts, Tag Cloud, Recent Links, Twitter status, and permalinks are all working as before. The new template doesn’t have a place for the randomly selected banner thumbnail images from my Flickr account, but does incorporate a larger random image at the top, which currently selects from a few photos I picked out of my snapshot collection. I may figure out some other way of sharing some photos here. I’ve also added a random quote widget. You have to provide your own collection of quotes, so there aren’t many in there yet.

It might be a little slower than the old platform for a while until I get the caching set up, all those customizable options use a lot of database queries.

Let me know what you think, and if you are have any suggestions or are having problems viewing things. I’ve mostly been looking at this with Firefox 3, so people with other browsers may have a different experience.

My Twitter follower tag cloud from Twittersheep

hjl twitter follower cloud
Twittersheep builds a tag cloud from the profile description of your Twitter followers. In my case, the tags suggest that many people following my Twitter feed are technology entrepreneurs and traders with an interest in markets and social media. Sounds about right.

via Webware

Cloud computing, infrastructure change, and Iron Man

Spent some time at CloudConnect last week. “Cloud computing” has an increasing amount of buzz lately. I notice that India is the top region and Korean is the top language for searches on the topic. The top 3 cities are Bangalore, San Jose, and Seoul. That sounds consistent with my impression of levels of interest and activity. Infoworld says “Cloud Computing shapes up as big trend for 2009″. It’s certainly turning into a hot label, although the underlying internet service infrastructure ideas have been around for a long time.

The current business environment is characterized by high uncertainty. However, assuming the global economy doesn’t totally collapse, companies that successfully migrate IT activities to the cloud can achieve lower costs and flexible scale, at the potential cost of vendor lock-in, regulatory uncertainty, and the operational risk of the transition itself.

Some of this reminds me of the dynamics around corporate ERP projects a decade ago. If you were the incumbent leader in your market, you’ve already invested in your line-of-business IT infrastructure, and it’s working. You may have even been an early adopter of ERP technologies, gaining time and experience in pilot projects to develop a competitive advantage in your in-house IT. At some point the other competitors in a given market end up in a difficult position – either continue as they are with a strategic disadvantage (no ERP), or take on a risky overhaul of their core IT systems and business processes to become more competitive (if the project succeeds). Kind of like Iron Man rebuilding the power supply for his heart and super-suit. It’s great, as long as it actually works. But it might kill you.

So who went down this path? The leaders tend to, because part of how they became the leaders in their markets is by looking for the next competitive edge, whether it is a technology, business process, or other. The interesting part is that in many ways it is more attractive for an *uncompetitive* company to attempt a radical technology and process overhaul, simply because what they’re doing is already *not* working. So it’s literally adapt or die. The implementation risks were substantial, sometimes companies suffered major setbacks through failed ERP adoption, Hershey’s being a the poster child for a disastrous SAP project, although it didn’t *quite* kill them.

Now let’s look at cloud computing. It is clearly a win for startups and insurgents in a given market. They gain IT capabilities and scale on par with all but the very largest organizations, and don’t have a sunk cost of equipment, staff, and existing business process. They can’t differentiate themselves on better IT per se, but they can develop their processes around the flexbility and scalability of the cloud, and design for competitive advantage within its constraints. They also have nothing to lose, so why not take the risk?

The more typical case is much more difficult. An existing enterprise already has substantial IT infrastracture assets, staff, and business processes. They will be severely criticized and probably sued if someone doesn’t like what they’re doing, which is problematic because they have an actual working business and assets. Nonetheless, in the current business environment, many existing organizations will be approaching that “adapt or die” point, in which the choices are to try something risky and maybe have it fail (in this case, moving IT services and processes to the cloud), or die (weighed down by higher costs and lower flexibility). One implementation risk is that the regulatory issues around privacy, security, accountability etc haven’t been worked out yet, and what major financial institution, bank, insurer, or health care provider would want to be the guinea pig in court? Not their first choice, but the prospect of lower incremental costs and the operating flexibility grow more and more appealing every day. Someone is going to be first, probably get sued, and then everyone will know what the rules are and jump in. Either that, or startups and insurgents in their markets are going to take over first.

140 characters is nice but doesn’t always work

I haven’t been posting here in a while, but think I will try picking up the keyboard here a little more frequently. I added a twitter box on the sidebar a while back, as I have been experimenting with that more, along with friendfeed, facebook, etc. I like the brevity and immediacy of twitter, but not everything fits in 140 characters. You can find me on twitter and friendfeed as “hjl”, also on Facebook.

HJL at the inauguration

HJL at obama inauguration

Me at Barack Obama’s inauguration, via FotoFlexer’s MyInauguralPhoto service. Just call me Zelig. (via TechCrunch)

Davis World Cup 2008

Flags at the 2008 Davis World Cup 

We spent the Memorial Day weekend at the Davis World Cup with the Palo Alto AYSO spring U12 girls team, the Blue Bandits. There were over 120 teams, and each team in the tournament gets the flag of a FIFA World Cup country. This is fun, but can make it difficult to figure out who you’re playing, as the schedules are all published under the names of the countries, not the actual names of the teams. We were “Bermuda”, although I spent the first day thinking we were “Bahamas.” 

The girls had a lot of fun. The highlight of the series was a rematch with the Concord Chaos (Tanzania),  who we tied 2-2 at last week’s Concord Cup. This weekend we placed 3rd in Bracket A, while the Concord Chaos placed 2nd in Bracket B, which put us in an elimination match to get to the next round.

Setting up for penalty shootout at the elimination round

The match was tied 1-1 at the end of the 2nd half, so the result was decided with a penalty shootout that ended the game in our favor 3-2.

We got knocked out of the tournament at the quarterfinals by Paso Robles (Uraguay) on Sunday afternoon, so no matches on Monday. Five games in two days was probably enough for most of the girls. They also went out to the movies together to see Narnia – Prince Caspian, visited the Davis Farmer’s Market, and probably had too much pizza and Jamba Juice.

U12G brackets A and B at Davis World Cup 2008 


Youth Soccer, From Above

The First Half - Youth Soccer - Rhymes With Orange 08-05-21  

A fine depiction of field positions in a typical youth soccer match, from Rhymes With Orange.



The inside of my Thinkpad T42p

The inside of my Thinkpad T42p 

This morning the IBM service tech came to replace the failed fan assembly in my Thiinkpad T42p. The Thinkpad has been fairly indestructable, having gone around the world several times without any problems. So I was surprised when I started getting “Fan Error” messages just after the BIOS splash screen while setting up on Sunday evening. Fortunately, I also got the 24-hour onsite support contract back when I got the system. It ended up taking more like 36 hours to get someone out here, but I did call in the middle of the night.

That reddish assembly at the middle left is the heatsink and fan. The system board runs a test to make sure the fan will spin up before proceeding with the system boot process; the original fan will spin manually, but the motor seems to have failed. I’m glad to have the technician replace the fan instead of doing it myself. Getting the heatsink off the graphics chip required some significant prodding with a sharp knife to unbond the heat compound sticking them together.

The past day and a half I’ve been using other computers around the office, which has been kind of strange. Even though they’re all part of my normal setup, nothing is in the right place, since I keep reaching or looking in a different direction than usual. It’s been like working in someone else’s office. This evening I’ve gotten everything synced back up, but probably need to start thinking about migrating off the Thinkpad at some point as it continues to age.

Google search results and DMOZ editorializing?

I’ve never seen a search result page like this before. The meta text “Conservative think tank claiming to report about events and nations strategically important to the United States” doesn’t appear any where in the referenced page, which doesn’t contain any useful <META> content. Searching for that text, it looks like the text originated from the DMOZ directory listing.

Another entry from the same DMOZ list, the Kensington Review, also returns the DMOZ meta text, this time in place of the <META> text in the actual page. DMOZ says “An e-magazine of political and social commentary. When the left says the glass is half full and the right says it is half empty, Kensington suggests that it might be too big.” Kensington’s own META says “An electronic journal of political, financial and social commentary”.  DMOZ is a more interesting description, but again does not originate from the content itself. 

So it appears that DMOZ editors have greater influence over certain Google search descriptions than the actual sites themselves, which is not necessarily bad, but was certainly unexpected (to me). Overall I’d prefer that Google limit its editorial function to ranking and presenting the search results, and perhaps make the editorial opinions known, but not presented as definitive. 

I’m not particularly familiar with the Jamestown Foundation, which is why I was searching in the first place. The DMOZ editor is clearly skeptical but I’d rather form my own opinion. 


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