Exploring biological network dynamics with ensembles of graph partitions.
Unveiling the modular structure of biological networks can reveal important organizational patterns in the cell. Many graph partitioning algorithms have been proposed towards this end. However, most approaches only consider a single, optimal decomposition of the network. In this work, we make use of the multitude of near-optimal clusterings in order to explore the dynamics of network clusterings and how those dynamics relate to the structure of the underlying network. We recast the modularity optimization problem as an integer linear program with diversity constraints. These constraints produce an ensemble of dissimilar but still highly modular clusterings. We apply our approach to four social and biological networks and show how optimal and near-optimal solutions can be used in conjunction to identify deeper community structure in the network, including inter-community dynamics, communities that are especially resilient to change, and core-and-peripheral community members. (+info)
Manifestations of personality in Online Social Networks: self-reported Facebook-related behaviors and observable profile information.
Use of anonymous Web communities and websites by medical consumers in Japan to research drug information.
In this study, we investigated the status of researching drug information online, and the type of Internet user who uses anonymous Web communities and websites. A Web-based cross-sectional survey of 10875 male and female Internet users aged 16 and over was conducted in March 2010. Of 10282 analyzed respondents, excluding medical professionals, about 47% reported that they had previously searched the Internet for drug information and had used online resources ranging from drug information search engines and pharmaceutical industry websites to social networking sites and Twitter. Respondents who had researched drug information online (n=4861) were analyzed by two multivariable logistic regressions. In Model 1, the use of anonymous websites associated with age (OR, 0.778; 95% CI, 0.742-0.816), referring to the reputation and the narrative of other Internet users on shopping (OR, 1.640; 95% CI, 1.450-1.855), taking a prescription drug (OR, 0.806; 95% CI, 0.705-0.922), and frequent consulting with non-professionals about medical care and health (OR, 1.613; 95% CI, 1.396-1.865). In Model 2, use of only anonymous websites was associated with age (OR, 0.753; 95% CI, 0.705-0.805), using the Internet daily (OR, 0.611; 95% CI, 0.462-0.808), taking a prescription drug (OR, 0.614; 95% CI, 0.505-0.747), and experience a side effect (OR, 0.526; 95% CI, 0.421-0.658). The analysis revealed the profiles of Internet users who researched drug information on social media sites where the information providers are anonymous and do not necessarily have adequate knowledge of medicine and online information literacy. (+info)
Using internet enabled mobile devices and social networking technologies to promote exercise as an intervention for young first episode psychosis patients.