Check out this article in BusinessWeek about Twitter. The article itself is pretty ordinary, but look at the spectacular number of hyperlinks it contains. In fact, there are so many links that the article is hard to read and I gave up.

I was wondering why having too many links in an article can be bad. I think it’s because when you encounter a link during reading, you have to think a little. What is this link about? Should I click it? Too many links makes for too much of this type of thinking, which makes reading the article hard. Also, the blue colour and underline of links is distracting. With so many distractions from the links, I couldn’t concentrate on what the BW writer was trying to say.

I wonder what the optimal ratio of links to words is. By my count, the BW article contains about 1,200 words and 42 links. My gut feeling says that one link per 100 words is about the maximum you’d want to have for a regular article.

(HT: Web 2.0…Really?)

Some random thoughts on a Friday afternoon …

In the beginning, all we had for one-to-many communication was text. Then we got audio (radio) and then video. Initially, these displaced text. Video, especially, is high bandwidth compared to text — more information can be communicated per unit of time (I think). However, high bandwidth also requires high attention. You cannot skim a video very easily. Then life got faster and faster, and along came the Internet. Video works on the Internet too, but people don’t have so much time for it. Hence, text is coming back, because although it is low-bandwidth, it is also low-attention.

Computers are dumb, and cannot understand the words on this page. A human could figure out that my blog is mostly about economics, but a computer would have a hard time doing this. The semantic web idea is trying to change this, by tagging or marking up content in a standardised way that makes it understandable in some sense to a computer.

One of the problems with implementing this idea is all the work that’s required to tag existing content. Rather than doing this manually, it would be more attractive if there is some automatic tag-generating system. However, there’s a chicken and egg problem, if the computer can’t understand the words in the first place, how can it understand them to tag them?

This is where something like Wikipedia comes in. Wikipedia is a collection of documents that have already been classified by humans into appropriate categories. By parsing the economics pages on Wikipedia, a computer can get some sense of what words are typically associated with economics content. With this “knowledge”, the computer could then scan other websites and determine which are about economics and apply appropriate keywords.

This seems to be a somewhat unexpected potential source of value for a site like Wikipedia. I wonder if it will spur further development of more traditional encyclopedias. Publishers of textbooks and the like may also have some valuable fodder for semantic algorithms.

SemanticHacker has a nice demo on their site of what can be done. Enter some text and it will try to identify what the text is about, and fetch related articles on Wikipedia.

Tyler Cowen points to an article about a guy who’s selling his Twitter account with 1500 followers on ebay. The auction is here and the current bid is a bit over $1500, i.e. around $1 per follower. To me this seems kind of high and is most likely affected by the publicity that this is getting. Certainly I wouldn’t pay $1 for a Twitter follower, especially not someone who’s originally chosen to follow someone else.

Anyway, it kind of illustrates how the flow of information is becoming increasingly decentralised. In the olden days, it used to be fairly obvious who the important sources of information were — major news organisations for the most part. To a large extent this is still true, but it’s changing rapidly. The old cliché about it’s not what you know but who you know that matters is becoming ever more true. The Internet reduces the cost of communication so much that economies of scale in information collection and distribution (e.g. that newspapers have) are a lot less important. In some sense this makes life harder, because it’s less clear who you should be listening to and who is a useful information provider. On the other hand there are benefits in that information providers become a lot more competitive.

As decentralisation of information sources increases, I think those who are effective “social hubs” will become more important and more powerful. Hubs centralise and filter information once again, and offset the tendency towards decentralisation. Hubs have both many sources and many followers. For a hub, it is not only who you know but who knows you that are important criteria for success.

Update: ebay have pulled the auction.

Three things happened in the past week:

1. I got invited to apply to join the new Forbes blog ads network.

2. A publisher’s rep e-mailed me to offer a free copy of a new book if I review it on my blog.

3. A publicist at The Washington Post started sending me a list of their top business stories.

I’m sure the top econ bloggers have been getting tons of requests like this for some time. What’s interesting is that major traditional media outlets are now starting to direct their attention to the second/third tier blogs like mine. It’s funny that it seems to have happened quite suddenly, or maybe just a coincidence.