Posts Tagged ‘tagging’

About the social semantic web

Web 2.0 – what´s next?

Yahoo Researcher Declares Semantic Web Dead – and reborn again…

When Mor Naaman from Yahoo said in a special track on Web 3.0 at WWW2007 that the “Semantic Web” is dead, he obviously tried to attract attention. Nevertheless, in my opinion he is absolutely right – there is no chance to “teach” people to annotate web content in a more sophisticated way than “social tagging” (and I´m pretty sure that also in the future it will always be a small community which will tag their content).

But in one point Mor Naaman missed the point: The “Semantic Web” was always there, under-cover more or less. Living in a tin with a lousy HTML-lid. And inside the tin there has always been enough semantics. There is no need to re-invent the data models, the namespaces, the ontologies (at least for most of the basic “things”) as Naaman proposes in his talk (slide 13). How easily all the existing semantics can be released and mapped against the “Semantic Web” (and suddenly it was born again ;-) ) is demonstrated by projects like [1] or [2].

May 17, 2007Posted by ablvienna | semantic web, tagging, web 3.0 | | No Comments

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Evolving Trends

July 2, 2006

Digg This! 55,500 hits in ~4 Days

/* (this post was last updated at 10:30am EST, July 3, ‘06, GMT +5)

This post is a follow up to the previous post For Great Justice, Take Off Every Digg

According to Alexa.com, the total penetration of the Wikipedia 3.0 article was ~2 million readers (who must have read it on other websites that copied the article)


EDIT: I looked at the graph and did the math again, and as far as I can tell it’s “55,500 in ~4 days” not “55,000 in 5 days.” So that’s 13,875 page views per each day.

Stats (approx.) for the “Wikipedia 3.0: The End of Google?” and “For Great Justice, Take Off Every Digg articles:

These are to the best of my memory from each of the first ~4 days as verified by the graph.

33,000 page views in day 1 (the first wave)

* day 1 is almost one and a half columns on the graph not one because I posted it at ~5:00am and the day (in WordPress time zone) ends at 8pm, so the first column is only ~ 15 hours.

9,500 page views in day 2

5,000 page views in day 3

8,000 page views in day 4 (the second wave)

Total: 55,500 in ~4 days which is 13,875 page views per day (not server hits) for ~4 days. Now on the 7th day the traffic is expected to be ~1000 page views, unless I get another small spike. That’s a pretty good double-dipping long tail. If you’ve done better with digg let me know how you did it! 🙂


This post is a follow-up to my previous article on digg, where I explained how I had experimented and succeeded in generating 45,000 visits to an article I wrote in the first 3 days of its release (40,000 of which came directly from digg.)

I had posted an article on digg about a bold but well-thought out vision of the future, involving Google and Wikipedia, with the sensational title of “Wikipedia 3.0: The End of Google?” (which may turn out after all to be a realistic proposition.)

Since my previous article on digg I’ve found out that digg did not ban my IP address. They had deleted my account due to multiple submissions. So I was able to get back with a new user account and try another the experiment: I submitted “AI Matrix vs Google” and “Web 3.0 vs Google” as two separate links for one article (which has since been given the final title of “Web 3.0.” [July 12, ‘06, update: see P2P 3.0: The People’s Google)


Neither ’sensational’ title worked.


I tried to rationalize what happened …

I figured that the crowd wanted a showdown between two major cults (e.g the Google fans and the Wikipedia fans) and not between Google and some hypothetical entity (e.g. AI Matrix or Web 3.0).

But then I thought about how Valleywag was able to cleverly piggyback on my “Wikipedia 3.0: The End of Google?” article (which had generated all the hype) with an article having the dual title of “Five Reasons Google Will Invent Real AI” on digg and “Five Reasons No One Will Replace Google” on Valleywag.

They used AI in the title and I did the same in the new experiment, so we should both get lots of diggs. They got about 1300 diggs. I got about 3. Why didn’t it work in my case?

The answer is that the crowd is not a logical animal. It’s a psychological animal. It does not make mental connections as we do as individuals (because a crowd is a randomized population that is made up of different people at different times) so it can’t react logically.

Analyzing it from the psychological frame, I concluded that it must have been the Wikipedia fans who “dugg” my original article. The Google fans did “digg” it but not in the same large percentage as the Wikipedia fans.

Valleywag gave the Google fans the relief they needed after my article with its own article in defense of Google. However, when I went at it again with “Matrix AI vs Google” and “Web 3.0 vs Google” the error I made was in not knowing that the part of the crowd that “dugg” my original article were the Wikipedia fans not the Goolge haters. In fact, Google haters are not very well represented on digg. In other words, I found out that “XYZ vs Google” will not work on digg unless XYZ has a large base of fans on digg.

Escape Velocity

The critical threshold in the digg traffic generation process is to get enough diggs quickly enough, after submitting the post, to get the post on digg’s popular page. Once the post is on digg’s popular page both sides (those who like what your post is about and those who will hate you and want to kill you for writing it) will affected by the psychlogical manipulation you design (aka the ‘wave.’) However, the majority of those who will “digg” it will be from the group that likes it. A lesser number of people will “digg” it from the group that hates it.

Double Dipping

I did have a strong second wave when I went out and explained how ridiculous the whole digg process is.

This is how the second wave was created:

I got lots of “diggs” from Wikipedia fans and traffic from both Google and Wikipedia fans for the original article.

Then I wrote a follow up on why “digg sucks” but only got 100 “diggs” for it (because all the digg fans on digg kept ‘burying’ it!) so I did not get much traffic to it from digg fans or digg haters (not that many of the latter on digg.)

The biggest traffic to it came from the bloggers and others who came to see what the all fuss was about as far as the original article. I had linked to the follow up article (on why I thought digg sucked) from the original article (i.e. like chaining magnets) so when people came to see what the fuss was all about with respect to the original article they were also told to check out the “digg sucks” article for context.

That worked! The original and second waves, which both had a long tail (see below) generated a total of 55,500 hits in ~4 days. That’s 13,875 page views a day for the first ~4 days.

Long Tail vs Sting

I know that some very observant bloggers have said that digg can only produce a sharp, short lived pulse of traffic (or a sting), as opposed to a long tail or a double-dipping long tail, as in my case, but those observations are for posts that are not themselves memes. When you have a meme you get the long tail (or an exponential decay) and when you chain memes as I did (which I guess I could have done faster as the second wave would have been much bigger) then you get a double-dipping long tail as I’m having now.

Today (which is 7 days after the original experiment) the traffic is over 800 hits so far, still on the strength of the original wave and the second wave (note that the flat like I had before the spike represents levels of traffic between ~100 to ~800, so don’t be fooled by the flatness, it’s relative to the scale of the graph.)

In other words, traffic is still going strong from the strength of the long-tail waves generated from the original post and the follow up one.



  1. Wikipedia 3.0: The End of Google?
  2. For Great Justice, Take Off Every Digg
  3. Unwisdom of Crowds
  4. Self-Aware e-Society

Posted by Marc Fawzi

Semantic Web, Web strandards, Trends, wisdom of crowds, tagging, Startup, mass psychology, Google, cult psychology, inference, inference engine, AI, ontology, Semanticweb, Web 2.0, Web 2.0, Web 3.0, Web 3.0, Google Base, artificial intelligence, AI, Wikipedia, Wikipedia 3.0, collective consciousness, digg, censorship


  1. Update this in two weeks, after a Friday, Saturday, and Sunday, and a holiday in the middle of the week in the United States which means a lot of people are on vacation, and another weekend, and see what happens with traffic trends, including Digg related traffic. And check out my unscientific reseach on when the best time and day to post is on your blog, and compare what you find over the course of time, not just a couple days. I’m curious how days of the week and the informal research I did might reflect within your information. That will REALLY help us see the reality of your success.Still, you’ve gathered a ton of fabulous information. I found it interesting that the post title on your Digg sucks article kept changing every hour or so on the WordPress.com top lists. I think it was “Power of the Schwartz” that really caught my eye. 😉

    I wish you could check out how much traffic came from WordPress.com dashboards and top blog listing comparatively to Digg traffic results, as well as all the other social bookmarking sources which pick up Digg posts, and compare that information as to how directly your traffic was related solely to Digg. It was in the first place, but “then” what happened.

    There is a lot of whack things that go into driving traffic, and I also know that WordPress.com’s built in traffic charts don’t match up exactly and consistently with some of the external traffic reports I’ve checked for my WordPress.com blog, so only time will tell, and this will get more and more interesting as time goes on.

    Good work!

    Comment by Lorelle VanFossen — July 2, 2006 @ 11:19 am

  2. Yeah I caught myself saying “Merchandising Merchandising Merchandising” the other day!:)

    Well I noticed about 1000, 800, 600, 500 hits (in this order) from WordPress for those 4 days …

    Valleywag sent me about 12,000 (in total)


    Comment by evolvingtrends — July 2, 2006 @ 11:26 am

  3. Great analysis on digg. It looks like digg or the memes can be somewhat influenced and analyzed. It’s almost like psycho analyzing a strange new brain.I find it very interesting how this all happened. Even if digg gave you a short pulse for a few days, it generated augmented daily traffic until now. I wouldn’t be surprised that new readers discovered you this way. The whole applications of traffic and readers are very fluid in nature. I wonder if they could be mapped in some way of form through fluid dynamics.


    Comment by range — July 3, 2006 @ 1:39 am

  4. It’s highly multi-disciplinary. It can be conquered but not as fast as you or I would like.This is like analyzing a strange new brain … a brain that is influenced greatly by everything except logic.

    I plan on analyzing it in the open for a long time to come, so stick around and add your thoughts to it. 🙂
    They say ‘observing something changes its outcome’ .. So we’ll see how it goes.



    Comment by evolvingtrends — July 3, 2006 @ 2:36 am

  5. […] 1. Digg This! 55,500 Hits in ~4 Days […]Pingback by Evolving Trends » Global Brain vs Google — July 3, 2006 @ 10:37 am
  6. […] This article has a follow-up part: Digg This! 55,500 Hits in ~4 Days […]Pingback by Evolving Trends » For Great Justice, Take Off Every Digg — July 3, 2006 @ 10:57 am
  7. Marc,I don’t know if this information helps or skews your research, but a post I wrote in January, titled to get Digg and other traffic attention, Horse Sex and What is Dictating Your Blog’s Content, did not do well at all. That is until the past three days.

    It’s really started piling up a lot of hits, sitting in the top 10 of my top posts, outreaching the other posts that get consistently high traffic by a huge margin. Until Saturday, that post was not even in the top 50 or 75. I can’t tell where the traffic is suddenly coming from, as WordPress.com doesn’t offer that kind of specific information, and I’m not getting any outstanding traffic from any single source. Nothing from Digg, but something is suddenly driving that post through the roof. Even during a holiday week in the US! Very strange.

    Maybe there’s a new fad in horse sex lately – who knows? 😉

    Still, the point is that this was written in January, and now it is getting attention in July. I’ll be checking to find out what is causing the sudden flush of traffic, but never doubt that your posts are ageless in many respects. So the long term study of Digg patterns and traffic will help all of us over the “long haul”. That’s why I’m really curious about the long term effects of your posts.

    Sometimes you just can’t predict the crowds. 😉 Or what they will suddenly be interested in. I’ve written so many posts and titles that I was sure would skyrocket traffic, only to lay there like empty beer bottles in the playground. Totally useless. And others with sloppy titles and written quickly with little attention to detail skyrocketing like 1000 bottles of coke filled with Mentos. 😉 It’s an interesting process, isn’t it?

    Comment by Lorelle VanFossen — July 3, 2006 @ 9:37 pm

  8. Predicting the weather for the long term is not currently feasible. However, predicting the weather for the short term is (1-2 days in davance.)But it’s not all about ‘predicting’ … It’s about studying the phenomenon so that we can make better choices to reduce the effect of uncertainty and not try to eliminate uncertainty.


    Comment by evolvingtrends — July 4, 2006 @ 12:02 am

  9. I think then that the obvious question is why you’ve done nothing to monetize those hits, however fickle they might be!;)

    Comment by Sam Jackson — July 4, 2006 @ 4:42 pm

  10. Monetize, Monetize, Monetize!Fortunately, that won’t happen 🙂


    Comment by evolvingtrends — July 4, 2006 @ 8:28 pm

  11. […] 4 – Digg This! 55,500 hits in ~4 Days A blogger explains how he ‘milked’ Digg for a major spike in traffic. Meme engineering in action; fascinating stuff. (tags: Wikipedia Google visits article post tail long spike scam traffic blogging blog meme Digg) […]Pingback by Velcro City Tourist Board » Blog Archive » Links for 05-07-2006 — July 4, 2006 @ 10:20 pm
  12. Since web traffic is dictated by humans and engines and not by some exterior force like the weather, I think that there are a lot of possible venues of analysis of it. The only thing is that the flow and traffic needs to be documented. In most cases, the traffic might be, but there lacks information on past flow. The internet is concentrated on the now and less with what happened ten days ago on this site and such.Mathematical Fluid dynamics are probably the way to go, though even if I am a mathematician, I’d have to research it a bit before pronouncing myself completely. These types of analysis can get quite complicated because of the implications of partial differential equations of an order higher than 2, which can not be solved only approximated numerically.

    I’m sure I’m not the only one to say this, but I like the types of discussions and content that you put forward, it gets the mind thinking on certain subjects that most of the time users tend to accept without question.

    Comment by range — July 4, 2006 @ 10:54 pm

  13. “the implications of partial differential equations of an order higher than 2, which can not be solved only approximated numerically.”Have you looked into Meyer’s methods of “invariant embedding” …? to convert PDEs to a set of ordinary differential equations then solve?

    I believe the investigation of hype management is extremely multi-disciplinary and very much like the weather. That means that while it’s deterministic (as everything is in essence with the exception of non-causal quantum theory) it’s still highly unstable and ultimately hard [in computationl terms] to predict.

    In general, uncertainty exists in every system, including maths itself (because of lack of absolute consistency and incompleteness), so while you can’t eliminate it you can hope to reduce it.

    But in practical terms, what I’m looking to do is to simply gain a sufficient minimum in insight to allow me to improve my chances at generating and surfing hype waves… I believe I will end up applying a non-formal theory such as framing theory to transform the problem from the computational domain to the cognitive domain (so I may use that 90% of the brain that we supposedly don’t use to carry out the computation with my own internal computational model.)

    Clarity, in simple terms, is what it’s all about.

    However, to reach clarity’s peak you have to climb a mountain of complexity 🙂


    Comment by evolvingtrends — July 4, 2006 @ 11:10 pm

  14. Hey Marc!I now know what it feels like to be caught in a digg like wave. Right now, I have had over 141000 page views because of a post that I did this morning, explaining HDR photography.

    Since digg banned my url for some reason (I don’t know why, I haven’t posted anything to digg in the last 2 months), this was all done through del.icio.us, Reddit and Popurls. It’s like one thing leads to another. I have added an url giving a surface analysis of this situation.


    Naturally, I find myself compelled to continue writing on the subject. I have already posted a follow-up article and I am working on another one right now. I knew I had a spike on weekends, nothing like this however.

    Comment by range — July 15, 2006 @ 7:29 pm

  15. Hey Marc.I think the main reason why I didn’t get any higher was because of the stat problem that WP has been having over the last few days.

    I hope they save this traffic so that I have some nice graphs to show you. They probably do. It felt like the counter was accurate, I checked out that I did indeed make onto a few memediggers, still am right now.

    And also the stat page was just so slow to catch up with the amount of traffic that was generated. WP couldn’t keep up.

    Hopefully, they will sort it out over the next few days. I think it was most surprising in the afternoon. I kept refreshing the counter, and oups, a few thousand here, ten thousand there. I was really surprised. And I have also started getting some haters, as you must know, with the good comes the bad.

    Comment by range — July 15, 2006 @ 8:49 pm

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Evolving Trends

June 9, 2006

Google 2.71828: Analysis of Google’s Web 2.0 Strategy

The title of this post should read Google 2.0, but in the tradition of Google’s college campus ads I decided to use 2.71828, which is the value of e (the base of the natural system of logarithms), in place of just plain 2.0.

So what’s all the fuss about? Google throws a bucket of AJAX (not the Colgate-Palmolive variety) on some empty Web page and people go “they must be doing something genius!” and then on and on goes the blogosphere in its analysis of Google’s latest move.

The Problem with Google’s Spreadsheets and Writely

First of all, for those who are not acquainted with the decades old concept of CVS (concurrent versioning system), being able to have multiple users edit the same document and enjoy all the benefits of version control is nothing new. Programmers have been relying on such systems for several decades now. And Wikipedia’s multi-user document editing and version control capabilities is just one popular example of CVS being applied it to Web documents.

What I find unusual/weird is that fact that Google’s Spreadsheet and Writely do not follow the established CVS model where a given document is protected from being edited at the same time by more than one user.

In CVS-like applications, like Wikipedia, many users may edit a given document but not all at the same time. Having multiple users edit a document, a program’s source file or an Excel spreadsheet at the same time (where there are many logical and semantic inter-dependencies across the document) can result in conflicting changes that create a mess. Changing an input value or formula in one cell or changing a global variable or a method in a program file (that’s called by other methods elsewhere in the program) will have effects elsewhere in the spreadsheet or program. If one person makes the changes then they’ll be able to track all places in the code that would get affected and make sure that their changes do not create bugs in the program or the spreadsheet. They would also comment it so that others understand what the change is. But if two people are making changes at the same time to the same spreadsheet or program (or document) and one person makes changes in one area that affects another area that the other person happens to be making changes to directly or indirectly, then you could see how that would lead to bugs being created due conflicting changes.

For example, let’s say I change A from 1 to 2 in area AA which I expect to change the value of B (which is defined as A + C and has an acceptable range of 0-4) from 3 to 4 in area BB but at the same time you (the second person editing the document) change C from 2 to 3 in area CC which you expect to change the value of B from 3 to 4 in area BB, then we would end up with B = 5, which neither of us would expect and which is outside the acceptable range of B, i.e. any value for B larger than 4 would break the calculation/program, thus creating a bug. This is the most simple case. In real practice the “multiple simultaneous changes” scenarios would be much more complicated and involve more logical and semantic inter-connections. In the scenario where two or more people can edit the same spreadsheet, document or program at the same time, if one cannot see the changes that the other person is making and understand their effect on all related parts of the program, spreadsheet or document then one should not be making any changes of their own at the same time, or else they would be creating havoc, especially as the number of people editing at the same time goes beyond two people. With two people it is conceivable that a system or process can be worked out where people can synchronize their editing. With three or more people the interaction process grows in complexity so much that it would require implementing a strict synchronization process (or a more evolved model) in the editing application to coordinate the work of the simultaneous editors so that mess can be avoided.

The CVS model, which is used by Wikipedia and other multi-user editing applications, avoids the mess that would be created by “too many chefs in the kitchen” by letting each document (or each “dish” in this case) be worked on by only one chef at a time, with each chef leaving notes for the others as to what he did, and with rollback and labeling capabilities. I find it unbelievable that a company like Google with such concentration of rocket scientists cannot see the silliness in letting “too many chefs work on the same dish” (not just in the same kitchen) without implementing the synchronization process that would be needed to avoid a certain, predictable mess.

What people really want for multi-user document editing is what Wikipedia already offers, which is consistent with the CVS scheme that has been so successful in the context of software development teams.

What people really want for multi-user spreadsheet editing is what DabbleDB already offers, i.e. to be able to create multiple views of the same dataset, and I would say also to be able to leverage the CVS scheme for multi-user editing where users may edit the same document but not at the same time!

The Problem with Google’s Strategy

In trying to understand Google’s strategy, I can think of three possible theories:

1. The “short range chaos vs. long range order” theory. This implies that Google is striving towards more and more order, i.e. decreasing entropy, as a long range trend, just like the process of evolution in nature. This means that Google leverages evolving strategies (as in self-organization, complextity and chaos) to generate long range order. This is a plausible way to explain Google’s moves so far. Knowing what we know about the creative people they’ve hired, I’m tempted to conclude that this is what they’re doing.

2. The “complicated but orderly” theory. Think of this as a parametric function vs. a chaotic pattern or a linear or cyclical one. This type of strategy has the property of being both confusing as well as constructive. Several bloggers have pointed to this possibility. But who are they distracting? Microsoft? Do they really think Microsoft is so naive to fall for it? I doubt it. So I don’t understand why they would prefer complicated over simple when it comes to their strategy.

3. The “total uninhibited decline” theory. This implies chaos in both the short and the long ranges of their strategy. Few people would consider this a possibility at this time.

It would seem that Google’s strategy falls under theory number one, i.e. they work with a large set of evolving strategies, trying to mimic nature itself. But whether or not they recognize this about themselves I have no clue.

So what if I was to convince a bunch of kids to take the Firefox source code and ideas from the GreaseMonkey and Platypus plugins and produce a version of FireFox that automatically removes all AdSense ads from Web pages and reformats the page so that there would be no empty white areas (where the Ads are removed from) … What would that do to Google’s ad-suported business model? I think it could do a lot of damage to Google’s model as most users hate having their view of the Web cluttered with mostly useless ads.

However, some say that Google Base is the Next Big Thing, and that’s an ad-supported model where people actually want to see the ads. In that case, it would seem that those bloggers who say Google’s strategy fits under theory number two (complicated but predictable) are correct.

Personally, I believe that Google’s strategy is a mix of both complex as well as complicated behaviors (i.e. theories number one and two), which is a sure way to get lost in the game.

Beating Google in Software as a Service (Saas)

As far as I can tell, Google 2.0 (or Google 2.71828 as I like to call it) has been mostly about SaaS.

Google is now to the SaaS industry what Microsoft has been to the desktop software industry. VCs are afraid to invest in something that Google may copy and co-opt.

However, just like how MS had failed to beat Quicken with MS Money and how they’ve failed to beat Adobe and Macromedia (which are one now) Google will fail to beat those who know how to run circles around it. One exit strategy for such companies may be a sale to Yahoo (just kidding, but why not!)

In general here is what SaaS companies can do to run circles around the likes of Google and Yahoo.

1. Let Google and Yahoo spend billions to expand their share of the general consumer market. You can’t beat them there. Focus on a market niche.

2. Provide unique value through product differentiation.

3. Provide higher value through integration with partners’ products and services.

4. Cater to the needs of your niche market on much more personal basis than Google or Yahoo can ever hope to accomplish.

5. Offer vertical applications that Google and Yahoo would not be interested in offering (too small a market for them) to enhance your offering.

Posted by Marc Fawzi

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Web 2.0, Ajax, Flex 2, Web strandards, Trends, RIA, Rich Internet applications, product management, innovation, tagging, social networking, user generated content, Software as a Service (Saas), chaos theory, Startup, Evolution, Google Writely, Google Spreadsheets, Google, DabbleDB, Google Base


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