Web 2.0 - Eine empirische Bestandsaufnahme

Anwendungen des Web 2.0 erfreuen sich großer Beliebtheit bei Benutzern und Investoren. Soziale Online-Netzwerke verfügen über Millionen von Mitgliedern, es werden über 100 Millionen Weblogs geführt, Millionen Menschen schauen sich täglich Videos und Bilder anderer Benutzer an. Trotz dieser beeindruckenden Nutzerzahlen ist die tatsächliche Bedeutung einzelner Anwendungen sowohl in quantitativer als auch in qualitativer Hinsicht oft noch unbekannt. Einzelne Fälle, in denen Aktivitäten im Web 2.0 dramatische Konsequenzen für Unternehmen oder einzelne Personen hatten, sind bekannt geworden. Handelt es sich dabei um Ausnahmen oder neue Regeln gesellschaftlichen Zusammenlebens? Dieses Buch versucht, Licht in die derzeitige Nutzung des Web 2.0 hineinzubringen.


Leseprobe:

5 Information Propagation and Self-Organized Consensus in the Blogosphere (S. 88-90)

Mei Zhu, Feng Fu, and Long Wang

1 Introduction

The recent development of the so-called network science reveals the underlying structures of complex networks and thus serves as a catalyst for the rising voice of interdisciplinary studies to tame complexity (Strogatz, 2001, Newman, 2003, Albert and Barabási, 2002, Boccalettia et al., 2006). The small-world network model proposed by Watts and Strogatz (1998) quantitatively depicts that most real networks are small worlds which have high clustering and short average path length. The "six degrees of separation," uncovered by the social psychologist Milgram (1967), is the most famous manifestation of small-world theory. The real world, however, signi.cantly deviates from the classic Erdös-Rényi model, in the sense that the degree distribution is right-skewed, that is to say, it follows a power law other than the Poisson distribution (Erdõs and Rényi, 1959, 1960, Barabási and Albert, 1999).

In particular, for most networks, including the World Wide Web (WWW), the Internet, and metabolic networks, the degree distribution has a power-law tail. Such networks are called scale free, and the Barabási-Albert (BA) model provides a possible generating mechanism for such scale-free structures: growth and preferential attachment (Barabási and Albert, 1999). These pioneering discoveries attract growing interest of researchers from different backgrounds. Besides, real networks are hierarchical and have community structures or are composed of the elements – motifs (Newman, 2006, Milo et al., 2002). Surprisingly, it is found that complex networks are self-similar, corresponding to the ubiquitous geometric pattern in snow flakes (Song et al., 2005).

Meanwhile, the dynamics taking place on complex networks such as virus spreading, information propagation, synchronization, evolutionary games, and cooperation have been deeply investigated and well understood (Watts, 1999, Huang et al., 2006, Pastor-Satorras and Vespignani, 2001, Acebrón et al., 2005, Barahona and Pecora, 2002, Motter et al., 2005, Zhou and Kurths, 2006, Santos and Pacheco, 2005). The word blog is short for the neologism "Web log," which is often a personal journal maintained on the Web (Cohen and Krishnamurthy, 2006). In the past few years, blogs are the fastest growing part of the WWW (Cohen and Krishnamurthy, 2006). There are now about 20 million blogs, which are emerging as an important communication mechanism by an increasing number of people (Butler, 2005).

The Web in its .rst decade was like a big online library. Today, however, it becomes more of a social web, not unlike Berners-Lee’s original vision. Consequently, advanced social technologies – Blog, Wiki, Podcasting, RSS, etc., which are featured as characteristics of the era of Web 2.0 – have led to the a change of the ways of people’s thinking and communicating. We refer to blogistan as blog space in the jargon of the blog field. As one surfs in blogistan, the global blogistan is just like an ecosystem called "blogosphere" that has a life of its own. In the view of complex adaptive systems, the whole blogosphere is more than the sum of its individual blogs.