The Structure of U.S. College Networks on Facebook

Anecdotally, social connections made in university have life-long impact. Yet knowledge of social networks formed in college remains episodic, due in large part to the difficulty and expense involved in collecting a suitable dataset for comprehensive analysis. To advance and systematize insight into college social networks, we describe a dataset of the largest online social network platform used by college students in the United States. We combine de-identified and aggregated Facebook data with College Scorecard data, campus-level information provided by U.S. Department of Education, to produce a dataset covering the 2008-2015 entry year cohorts for 1,159 U.S. colleges and universities, spanning 7.6 million students. To perform the difficult task of comparing these networks of different sizes we develop a new methodology. We compute features over sampled ego-graphs, train binary classifiers for every pair of graphs, and operationalize distance between graphs as predictive accuracy. Social networks of different year cohorts at the same school are structurally more similar to one another than to cohorts at other schools. Networks from similar schools have similar structures, with the public/private and graduation rate dimensions being the most distinguishable. We also relate school types to specific outcomes. For example, students at private schools have larger networks that are more clustered and with higher homophily by year. Our findings may help illuminate the role that colleges play in shaping social networks which partly persist throughout people's lives.Comment: ICWSM-202

Trust Propagation with Mixed-Effects Models

Web-based social networks typically use public trust systems to facilitate interactions between strangers. These systems can be corrupted by misleading information spread under the cover of anonymity, or exhibit a strong bias towards positive feedback, originating from the fear of reciprocity. Trust propagation algorithms seek to overcome these shortcomings by inferring trust ratings between strangers from trust ratings between acquaintances and the structure of the network that connects them. We investigate a trust propagation algorithm that is based on user triads where the trust one user has in another is predicted based on an intermediary user. The propagation function can be applied iteratively to propagate trust along paths between a source user and a target user. We evaluate this approach using the trust network of the CouchSurfing community, which consists of 7.6M trust-valued edges between 1.1M users. We show that our model out-performs one that relies only on the trustworthiness of the target user (a kind of public trust system). In addition, we show that performance is significantly improved by bringing in user-level variability using mixed-effects regression models

European Dialogue Report. Lessons from ten low-carbon dialogues

The R&Dialogue project has facilitated ten low-carbon dialogues with representatives from energy, the low-carbon R&D community, social actors and others. In each of the ten countries involved, a ‘coalition of the willing’ explored the challenges and articulated their view on improving the dialogue. This European Dialogue Report is a collection of these experiences, and it reflects upon the themes emerging from those dialogues

A vision and action plan for a low-carbon Europe

The European vision outlined, which is only one of many visions possible, is a result of a three year learning process. The R&Dialogue consortium discussed the experiences made and lessons learned during the ten country dialogues. Based on these findings an overall vision for Europe has been constructed. The vision tries to highlight the insights of this mutual learning process, but clearly it does not necessarily reflect the opinions and interests of all the external stakeholders involved. The chapter ‘Vision for Europe in 2050’ lays out the characteristics of a possible low- carbon Europe in the future. The chapter ‘Ways of getting to the low-carbon society’ gives recommendations for how to achieve this transition