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How did the absence of mobile phones affect the romantic life and death of Shakespeare's Romeo and Juliet? The difference in their situation would have been part of the social change to networked individualism from group-based societies. The Mobile Revolution would have afforded personal communication rather than the household-centered communication of the Montagues and the Capulets. Romeo and Juliet would have been always available to each other, instead of wondering where the other might be. Location-aware apps would have plotted their whereabouts. The course of true love would have been more connected.

There is some panic in the United States about a possible decline in social connectivity. The authors used two American national surveys to analyze how changes in the number of friends are related to changes in Internet use. The authors found that friendships continue to be abundant among adult Americans between the ages of 25 to 74 and that they grew from 2002 to 2007. This trend is similar among Internet nonusers, light users, moderate users, and heavy users and across communication contexts: offline, virtual only, and migratory from online to offline. Heavy users are particularly active, having the most friends both online and offline. Intracohort change consistently outweighs cohort replacement in explaining overall growth in friendship.

What is the Internet doing to local community? Analysts have debated about whether the Internet is weakening community by leading people away from meaningful in‐person contact; transforming community by creating new forms of community online; or enhancing community by adding a new means of connecting with existing relationships. They have been especially concerned that the globe‐spanning capabilities of the Internet can limit local involvements. Survey and ethnographic data from a "wired suburb" near Toronto show that high‐speed, always‐on access to the Internet, coupled with a local online discussion group, transforms and enhances neighboring. The Internet especially supports increased contact with weaker ties. In comparison to nonwired residents of the same suburb, more neighbors are known and chatted with, and they are more geographically dispersed around the suburb. Not only did the Internet support neighboring, it also facilitated discussion and mobilization around local issues.

The article analyses the transfer of biological, computer and marketing viruses. Despite differences between these three types of viruses, network structure affects their spread in similar ways. The authors distinguish between two forms of networks - densely knit and ramified - and show that biological, computer and marketing viruses all behave in similar ways depending on the form of network. Densely knit networks promote the quick dissemination of a virus, and increase the odds that many of the members will become infected. Ramified networks allow a virus to disperse widely, jumping between different milieux. In the end, the spread of viruses in the real world involves a combination of both densely knit and ramified networks, which the authors call 'glocalization'.

The authors examine the experience of the residents of Netville, a suburban neighborhood with access to some of the most advanced new communication technologies available, and how this technology affected the amount of contact and support exchanged with members of their distant social networks. Focusing exclusively on friends and relatives external to the neighborhood of Netville, the authors analyze community as relations that provide a sense of belonging rather than as a group of people living near each other. Computer-mediated communication (CMC) is treated as one of several means of communication used in the maintenance of social networks. Contrary to expectations that the Internet encourages a global village, those ties that previously were just out of reach geographically experience the greatest increase in contact and support as a result of access to CMC.

L'utilisation de SAS pour convertir des réseaux ego en réseaux complets. Cet article présente une technique utilisant le logiciel SAS pour convertir des données de réseaux centrés sur des individus (réseaux ego) en données de réseaux complets de relations. Jusqu'à maintenant, ces deux types de réseaux ont été généralement analysés séparément et avec des méthodes distinctes.