Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization). The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in the Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for the Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities.

We consider the question whether pupils from the lower social strata perform better in private government-dependent schools than in public or private-independent schools, using the Programme for International Student Assessment (PISA) 2000 data on European high schools. In the 1980s, Coleman and Hoffer ( 1987 Coleman, J. S. and Hoffer, T. 1987. Public and private high schools. The impact of communities, New York: Basic Books. [Google Scholar] ) found in the USA that the performance of these pupils was better at religious schools than at comparable public schools. Dronkers and Robert ( 2003 Dronkers, J. and Robert, P. 2003. The effectiveness of public and private schools from a comparative perspective, San Domenico di Fiesole (Fi): European University Institute. EUI working paper SPS 2003/13. Retrieved May 1, 2004, from http://www.iue.it/PUB/sps2003-13.pdf. A revised version was presented at “Session International Perspectives on the Sociology of Education” at the annual meeting of the American Sociological Association, San Francisco, August 14 – 17, 2004. Retrieved May 1, 2004, from http://www.iue.it/Personal/Dronkers/English/pisaprivate.pdf [Google Scholar] ) found in PISA data for 19 comparable countries that private government-dependent schools are more effective than comparable public schools, also after controlling for characteristics of pupils and parents and the social composition of the school. The main explanation appeared to be a better school climate in private government-dependent schools. Private independent schools were less effective than comparable public schools, but only after controlling for the social composition of the school. As a follow-up we now investigate, again with the PISA data of these 19 countries, whether this positive effect of private government-dependent schools differs between pupils from different strata. We use various indicators to measure social strata: social, cultural, and economic. We expect that the thesis of Coleman and Hoffer does hold for private government-dependent schools because in these 19 countries they are mostly religious schools, which have more opportunities to form functional communities and create social capital. But for private independent schools, which because of their commercial foundation are less often functional communities, this relation is not expected to hold. However, the results show that public and private schools have mostly the same effects for the same kind of pupils and thus mostly do not favor one kind of pupils above another kind of pupils. But private government-dependent schools are slightly more effective for pupils with less cultural capital and private independent schools are also more effective for pupils from large families or low status families.

While pandemic containment measures benefit public health, they may jeopardize the social structure of society. We hypothesize that lockdowns and prolonged social distancing measures hinder social support and invite norm violations, eroding social trust. We conducted a pre-registered pre-post study on a representative sample of the Dutch population (n = 2377; participation rate = 88.8%), measuring social trust reported by the same individuals before and after the first wave of the COVID-19 pandemic. Results show that social trust in the Netherlands suddenly dropped from its historically stable level, reaching one of its lowest points on record. The decline was stronger among residents belonging to official high-risk categories, especially if they perceived themselves as likely to become infected. Individuals who more strongly agreed with self-isolation norms or did not perceive a widespread compliance or agreement with such norms also reported a greater loss of trust.

Buyers and sellers of illegal drugs in cryptomarkets have been found to overcome trust issues created by anonymity and the lack of legal protection with the help of reputation systems. Cryptomarkets rarely operate for longer than a year before closing or getting shut down due to external shocks, such as law enforcement operations. This results in large flows of users migrating between market platforms. An important question in order to better understand why cryptomarkets recover quickly after external shocks is: to what extent can reputation be carried over between different markets? This problem is non-trivial given the anonymity of cryptomarket users and the fact that reputation is tied to a user's online identity. Here we analyze conditions under which sellers choose to migrate with the same identity and whether reputation history from previous cryptomarkets yields benefits in new contexts. We analyze sellers' migration in three cryptomarkets (Abraxas, Agora and AlphaBay) and follow their reputation history by linking user accounts between marketplaces using the Grams database. We use longitudinal multi-level regression models to compare market success of migrant and non-migrant sellers. In total, the data contains more than 7,500 seller account and 2.5 million buyers' reputational feedback messages over a period of 3 years. It is predominantly the successful sellers with a large number of sales and high reputation who choose to migrate and maintain their identity using cryptographic methods after market closures. We find that reputation history from previous markets creates a competitive advantage to migrant sellers compared to market entrants. Reputation transferability embeds cryptomarket users beyond a single market platform, which incentivizes cooperative behavior. The results also suggest that reputation transferability might contribute to a quick recovery of online drug trade after shutdowns and accumulation of market share in the hands of a small fraction of successful sellers.