Recently in a post about ‘network theories in the blogosphere‘, I explained how the web listens to the linking methods of the network.

Yesterday Terry Heath wrote an interesting article about reciprocal links in a blog. Really enlightening stuff.

But there’s one point I disagree with:

He suggests finding potential link partners and sending them a small introductory text, where you say that you have an active link of their site and that you would appreciate a link back.

It’s not that I find the method bad or ‘marketing-like’, its just that i prefer people linking to me, because they found my post interesting; because they thought I had something to say that passes with their post (regardless if its a disagreement or a praise).

I believe that’s the main reason blogs have developed trackback, right?

Now you might say, that I’m writing this post to get a reciprocal link from Terry Heath. It could be so, but its up to him if he links back to me or not. I’m not offering an exchange. I’m opening a discussion.

Teut Weidemann was the head of community development for panzer elite and for the entire jowood community. He started in the games business in 1987, but worked on computers since 1981. Several months ago, while I was working on GameFace magazine, I had the opportunity to interview him, about community building and management. Although the topic was mostly video game communities, he suggested that his ’strategies’ …”can be used for all communities, from games to fans of tv series to bookkeepers”.

I found the article yesterday, and I wonder if his suggestions can also be applied to blogging communities? Judge for yourself:

What do you actually mean with community management? What is it basically about?

Community management is the task to manage and support your community members. If you don’t support or manage them your community will fall apart. So you have to have someone who cares about them and knows how a community works. That’s one part of community management. The other part is how to plan the information flow to your community. How do you plan it, manage it, and control it all for the benefit of your community. After all your community is your customer right in from of your doors. Don’t shy him away.

Do companies that create communites mainly for marketing reasons, handle them differently as developers that create them for fun?

Yes, the firtst ones will fail, the second will succeed (strangely to any observer). Building up communities just for marketing won’t work. The community only grows if they gain something, something they can’t get elsewhere. That’s why developers have a build in talent to manage communities right: they love to talk about their game so they share a lot of information with the community.

Communities aren’t stupid, in fact with most communities there are people more talented and smarter than in the complany who manages that community. So don’t try to feed them false info, or worse don’t try to market talk to them. They hate it. Open, uncensored, truthful, straightforward and in time. That’s what your information needs to be.

What is the role of the community manager? Is he supposed to interfere in the whole process of the community?

The community manager is the interface between your community and the people behind the product. He needs to know all about the product and has to have access to all people involved in it. He doesn’t control the community, he supports it. Total control will destroy a community pretty fast. Of course he needs to take control if things get out of hand, but that’s rare and only shows to things if it happens: Your community is getting large (and part of it are troublemakers) or you have done something wrong. A community manager only interferes if there are problems the community can’t solve for themselves. Some problems of the community are made by the owners of the product. Either they released wrong information or no information at all. Leaving the community alone and not giving them something to feed on is a mistake. Not listening to them is a mistake, too. Not intergrating them into your product feedback is a waste of potential.

Is there a principle for the ideal time to post news, where they will be mostly read? If so, how does this principle work and what is it based on?

Yes, most news are read on Mondays as people browse the news during office hours. On weekends it’s bad as most people rather play than browse. But Monday is very crowded as many news from the weekend are being posted. So we picked Tuesdays and Thursdays to post. Sometimes however we used Fridays as the news will stick on the sites for the whole weekend. We got access to the number of news readers and clearly saw when we had most feedback (i.e. visitors from other sites due to our news) which showed exactly when it was optimal to post. That might vary depending on the product. For a TV Show for example, it would be important to post around the air time of the show, for games its different: Gamers bahavior can be measured and you should follow it to maximize your efforts.

What reasons would make a good community fall apart, even though the manager has followed the strategy rules?

Lack of new information, no one to talk to, bad product being released not fulfilling the promises (break of the rule being truthful, remember?), change of site with registering, changing too much on the site too often, not caring. Many things, some little and some big ones you can do wrong.

This is just a part of the whole interview. We also talked about the relation of community management and product value, marketing inside the community and the role and taks of the community manager. If you’re interested in reading the whole thing let me know.

I am wondering if google and its search engine are actually important for the blogosphere. I believe, that bloggers have lots of options to locate other blogs (technorati, feedster, etc) and google is not the only solution.

Under that perspective, I completely agree with the post in the blog herald about the google game.
Google is not the only game in town, and even if it were, blog entries should be targeted to the readers.

Nonetheless, getting acquainted with google’s pageranking system can certainly help understanding how the network works. Apart from that, I suppose that other search engines, rank sites more or less on the same principles.

So here are a couple of links, which explain google’s pagerank algorithm. One here and one here. Both posts are very detailed and surely explain a lot (although concentration is needed).

As the post in the blog herald suggests, I have my doubts if the algorithm is completely decoded, but still both posts are extremely thorough.

If you imagine the social web as a gigantic town meeting, you could presume that the number of inbound (trackback) and outbound links (blogroll) can define its size. Taking a short look at network theory, from its very beginnings to contemporary studies, will show how this interconnected city works. Networks can be found literally everywhere: in airports and airplane traffic, in our brain, in micro-organisms and even in social interactions. Network theory has evolved in a study proving that we are living in a connected age where ‘everything is connected to everything else’. Seeing the multitude of networks existing you can logically assume that there isn’t just one type of network. Depending on its structure and the behavior of its nodes, a network develops specific characteristics. So let’s introduce these networks, follow their expansion and consequently observe the characteristics of the blogosphere (and their meaning too!).

The type of network our town constitutes, can define the relationships and interactions in it. For example, if the members of the community are all randomly connected – each of them having on average one friend (link) – we result in a distribution where a large number of members (nodes) have almost the same number of friends (links).

Random networks

It is a theory developed by Paul Erdòs and Alfred Rènyi in 1959, called random graph theory. It relies on clustering, that is to say that most people’s friends are also to some extent friends of each other [Duncan J. Watts; Six Degrees]. It explains that the connection of small groups (clusters) will result into a single giant component. In a random network each node can contact any other node in very few steps and the more nodes the network has, the harder it is to find an isolated one.
If you want to translate random networks in attentiveness, the theory implies that drawing the attention of the public (namely the other nodes) is not such a complicated process. Everyone on the system receives more or less the same amount of links, namely interest. If you were to create a blog in a random network, sooner or later you would have roughly as many viewers as Google has. But we know (experience says) that the blogosphere - and the Internet in general - that we are not dealing with a random network. You do not randomly link to other blogs in your blogroll (or do you?), you choose them according to your interests and preferences. Therefore a new approach should be considered.
What random network theory did not take into account, was that most real networks (organisms, social relations, the web, etc.) are not static objects. New links are constantly created, while old ones abandoned. Apart from that, clustering takes place by virtue of individuals having a number of affiliations, which are not all equally alike, meaning that our new acquaintances depend sometimes from our old ones. Indeed our actions directly deprive from our characteristics and these actions may lead us to completely new connections, which have no relation to our previous ones.

[Both pictures taken from the book 'Linked' from Albert-Làszlo Barabàsi]

Scale Free Networks

In 1998 Albert-Làszlò Barabàsi with his co-workers were having their doubts, if the web was actually a random network (as thought until then). They started by creating a map of the internet (in reality a representational part of it), to research if its structure complied with the random model. They noticed that on the one hand 80% of the nodes researched had an average of four links while on the other hand 0.01% had more than 1000 links.
The architecture of the World Wide Web, Barabàsi’s group concluded, is dominated by few highly connected hubs (like Amazon.com, or Google). These hubs are visible to everyone – there is a link in most sites pointing to them. On the other side there are sites, which are on the borders of the map, receiving almost no attention at all. Such a network (named scale-free network) follows a power law distribution. It is a continuously decreasing curve, which shows that many nodes have a few incoming links, while a few hubs have a lot.

Attributes of scale free networks

A primary property of scale-free networks and the power law distribution is that the rich get richer. This happens because we usually prefer to link to webpages that are not ordinary nodes, but hubs. If you want to point to an online shop, the chances are you would point to Amazon. This means, that the more links a site attracts the more popular it gets and the more easier it is to find it.
But, this also implies that the oldest node on a network will always have the most incoming links, since it had the longest time to collect them. Still, we have seen examples of sites and blogs, which although not popular when first online, receive great amount of attention, sometimes over night. This happens due to the webpage’s ability to offer better content, updates, or services than its competitors. In such case of a competitive environment, each node has a certain fitness a degree, which defines how often the node will be linked. For example, between two nodes with the same number of links, the fitter one acquires links more quickly. While an old site might still draw attention of the users, a fit one will do so much faster. In other words, seniority is a great asset to draw interest, but fitness – which is independent of seniority - defines the speed at which nodes acquire links and therefore a senior node is not necessarily – or will eventually not be - the most popular.

[a good introduction to the subject was written by Michael Schuster; it helped me a lot // also a good article with nice recommendations was written by Jason Kottke]

What do scale-free networks tell us

• First of all the obvious. If you want to get heard in the blogosphere, you need lots of links - inbound and outbound. That the blogosphere is actually a competitive environment (whether we accept it or not) and we are all competing for links.That content can have a great deal of impact. And by content I don’t just mean text, but any type of services you could provide. May it be fancy CSS stylesheets, theoretical articles, beautiful pictures, groovy videos. If your fitness degree is high, you have nothing to worry about.

From the beginning of the twentieth century until today, a series of laws has emerged concerning the growth of computers and networks. They all negotiate the value of a network according to the technological leverage of the time. A short introduction to these laws, will prove why social media and collaborative communities can potentially grow into much larger networks than any other system.
Sarnoff’s law, which was interested with the growth of radio and television networks (and said that the system grows according to the amount of users constituting it) was followed by Moore’s law handling the evolution and expansion of computer microchips. Some years later, with the introduction of ARPANET and the first connected computers, Bob Metcalfe proposed a new law describing the value and the growth of networks.[as explained in the blog of VC Mike]

The law suggests that the value of a network grows with the square of the number of nodes (namely devices or people) it connects. It proposes that the number of potential connections between nodes grows faster than the actual number of nodes. If we have for example four nodes in a network, they will have a value of sixteen.

[When N the number of nodes, Metcalfe's law suggests that the network expands in a rate of N²; see Simeon Simeonov's post for more information] // [Value, according to David Reed, takes the form of potential connectivity for transactions. Namely, the number of different access points (users), which any particular user can connect to]

David Reed studied Metcalfe’s law and noticed, that although it describes telephone systems or small ethernet networks very well, it cannot be applied to social, group-forming networks such as the internet. The reason is, that Metcalfe’s law does not take into account the ability of the people in the network to form groups. Considering this, Reed discovered that “…networks that support the construction of communicating groups create value that scales exponentially with network size, i.e. much more rapidly than Metcalfe’s square law”. For example, according to Metcalfe’s law the value of ten users is one hundred (ten to the second power) and according to Reed’s Law 1,024 (two to the tenth power).

Illustration found at http://spectrum.ieee.org/print/4109

We see that both Metcalfe’s and Reed’s laws are associating the linkage of a network with its value. The connections in a system multiply faster the more users are part of it. Reed’s law assigns one more variable to this thesis. It declares that in a networked system, participation can exponentially boost its value. Though at first this increase may be small, it can eventually grow rapidly – and indeed faster than any other power law. Under that perspective, it is logical to assume that the possibility of group forming networks to expand into vast interconnected systems, systems that can function as hubs in the social web, is much higher than any other non-social network.

The transition that we are witnessing in traditional hubs (Amazon.com, google, etc.) verifies this assumption. These sites were providing services, which could be understood under Metcalfe’s law. They were connecting people and sites, but they were not giving them the option to form their own communities. But the rise of group forming networks and their expansion potential forced these sites to change. Amazon is now providing user review services and google several blogging and document sharing functions. These traditional hubs saw that social networking has the ability to create rapidly a vast system; a fact that made ‘fit’ (fitness as expressed by Albert-Làszlo Barabàsi) social websites strong competitors. The only way to stay on top was to add group forming services, which would allow the development of their network and keep users interested.

In Conclusion

There has been a great controversy about the role of Metcalfe’s law in the internet and if it actually can be applied to it. But if we disregard this debate and go a little bit further to Reed’s Law, we will see that a network, which encourages user interaction and group formation is able to grow much faster than other networks and - as I previously noticed - faster than any power law. This may be a mathematical explanation, why the blogosphere has grown so rapidly. It includes the parameter of socializing; blogs do not connect only computers but also people.

But its development makes me nonetheless wonder: In what frequency and degree does interaction between bloggers actually take place? Is the blogosphere also evolving in a ‘one-to-many’ medium or does the social aspect constantly win ground?