Twitter and its networking (in)capabilities
Nowadays, many of the popular social network sites are advanced platforms that more or less evolved from simple community platforms or fora. Where Myspace, Friendster and The WELL (later the Dutch De Digitale Stad popped up as a similar landmark) took off during the 90’s, Facebook, Hyves and hybrids (Morgan Currie earlier elaborated on this subject) like Last.fm emerged. These latter cases did benefit from the post-bubble internet revival that was presented as Web 2.0. As the 2.0 philosophy was fundamentally always present in the social network configuration, the emphasis for the new branch of services is much more on the facilitation of vast networks of interconnectivity. In practice, this results in tools which enable users to ‘network’ more effectively. The systems’ algorithms, along with its databases, needed to be revised to give new users a kind of starting-point for this manifestation. This is made clear by the directed recommendation-systems that basically scans and compares the different user-profiles. However, as of today this often results in plain and predictive references that depend on singular data. By saying this I’d like to exclude the Last.fm ‘neighbours’-technique, as it focuses not on the personal data, but rather on the capturing over time that generates a more accurate listening-profile.
As the current network sites streamline this connectivity of nodes differently, there’s a devious (though popular) network in the uprise: Twitter. Often described as a ‘microblog tool’, I find this case to be evenly (or more) a networking tool, since it (according to the Wiktionary definition) somewhat facilititates “the act of meeting new people in a business or social context”. I use the word ‘somewhat’ because the software is never genuinely transparant on the interconnectivity of its users, and doesn’t recommend similar users as on the other network sites. The system could easily be critized for the usage threshold, since the many of the real successors seem to be already established celebrities or people who tend to work in marketing or networking-reliant sectors. There also are numberous of blogs and books dedicated to the subject of effective networking on Twitter, this tendency also underlines the difficulty of positioning and maintaining accounts properly. Then again, this does not in any way exclude other low-end usage from being capable within the network, though it does identify the system as not very accesible in terms of communication.
Another obstacle in this efficient way of networking is formed by the active mode the platform demands from its users. The user’s networking strategies (consisting of medium literacy) fully determine for the succes or lack of it, this entirely breaks with the passive profiling tradition that encompasses filling in profile endless webforms or by protocological input. On Twitter, profiling is much more inferior to the actual (140-character) microblogging it facilitates. In this sense, the user profile becomes less of a static ‘personal branding poster’, but rather a representation over time. No longer is the user’s profile fixed on just one conception, it could be stated the Twitter microblog is inherently positioning the users more as a organic – being able to adept or adjust thoughts over time in the form of updates.
This character of real-time (or real-life) streams of data causes new challanges in terms of the abilities for sustainable networks to develop. This is partially why the previously mentioned marketeers are so eagering to develop efficient networking-tools, as their business largely consists of consultancy and services. Sites like Mr. Tweet have already begun on programming toolsets, although they rely too on the old tradition of comparing biographical information instead of the actual messages. One of the current tools to plow through the information masses is by using Twitter’s search function. Although this search engine offers some advanced features, it again demands dito query input. One might impose that this is an effective way to find anyone regardless of the updating behaviour, but the fact is high-end users obviously dominate pushing more passive users below the surface.
Another option is to index your the followers of the people you already follow, which again can turn out to be a arbitrary task. This method again pushes the super-connectors forward, leaving the incidental encounters as the network’s structure remains more or less hidden.
In conclusion maybe Twitter could (or should) be seen as a more hybrid network, as it mainly connects users on the basis of their updating behaviour (leaving out the super-connectors) that leads to the unpredictable network dynamic. Ironically, the system doesn’t connect anyone to anything by itself and simply eludes the term ‘friends’ in the node-to-node relation in contrast to ‘old’ networking-sites, which makes it all more confusing for low-end users. In future research, the actual relations between the user’s productivity and the criteria for emerging interconnectivity should be outlined more clear, as well as an outline of the obstacles in the development of networking tools, as those would have to rely more on the language than on profiling in the case of Twitter.