Keeping up with the e-Joneses: Do online social networks raise social comparisons?

Online social networks such as Facebook disclose an unprecedented volume of personal information amplifying the occasions for social comparisons. We test the hypothesis that the use of social networking sites (SNS) increases people's dissatisfaction with their income. After addressing endogeneity issues, our results suggest that SNS users have a higher probability to compare their achievements with those of others. This effect seems stronger than the one exerted by TV watching, it is particularly strong for younger people, and it affects men and women in a similar way.Comment: 25 pages, 5 figure

Proceedings of the 11th European Agent Systems Summer School Student Session

This volume contains the papers presented at the Student Session of the 11th European Agent Systems Summer School (EASSS) held on 2nd of September 2009 at Educatorio della Providenza, Turin, Italy. The Student Session, organised by students, is designed to encourage student interaction and feedback from the tutors. By providing the students with a conference-like setup, both in the presentation and in the review process, students have the opportunity to prepare their own submission, go through the selection process and present their work to each other and their interests to their fellow students as well as internationally leading experts in the agent field, both from the theoretical and the practical sector. Table of Contents: Andrew Koster, Jordi Sabater Mir and Marco Schorlemmer, Towards an inductive algorithm for learning trust alignment . . . 5; Angel Rolando Medellin, Katie Atkinson and Peter McBurney, A Preliminary Proposal for Model Checking Command Dialogues. . . 12; Declan Mungovan, Enda Howley and Jim Duggan, Norm Convergence in Populations of Dynamically Interacting Agents . . . 19; Akın Günay, Argumentation on Bayesian Networks for Distributed Decision Making . . 25; Michael Burkhardt, Marco Luetzenberger and Nils Masuch, Towards Toolipse 2: Tool Support for the JIAC V Agent Framework . . . 30; Joseph El Gemayel, The Tenacity of Social Actors . . . 33; Cristian Gratie, The Impact of Routing on Traffic Congestion . . . 36; Andrei-Horia Mogos and Monica Cristina Voinescu, A Rule-Based Psychologist Agent for Improving the Performances of a Sportsman . . . 39; --Autonomer Agent,Agent,Künstliche Intelligenz

An analysis of adolescents\u27 and young adults\u27 support networks.

This study examines adolescents\u27 and young adults\u27 support networks and the importance of support to their well-being. One hundred and sixty subjects, distributed across four age groups (15--16, 17--18, 20--22, 25--27 years old) completed a semi-structured interview assessing their worries, stressful life events, and received support. They also completed self-report measures of perceived support, life stress, and well-being. Results revealed significant main effects and interactions across age, sex, race, and SES. For instance, the youngest group was more likely than the other three age groups to receive no support. Females were found to receive more emotional support. However, the youngest males received more emotion focused support across age. Whites were found to have larger support networks than African-Americans. Whites and adolescents of middle SES were found to more often turn to professionals while male African-Americans of low SES more often turned to religious figures. Perceived support and social integration were found to be positively related to well-being. Results are discussed in terms of their implications for healthy adolescent development. Source: Masters Abstracts International, Volume: 39-02, page: 0609. Adviser: Rosanne Menna. Thesis (M.A.)--University of Windsor (Canada), 2000

The Effect of Collective Attention on Controversial Debates on Social Media

We study the evolution of long-lived controversial debates as manifested on Twitter from 2011 to 2016. Specifically, we explore how the structure of interactions and content of discussion varies with the level of collective attention, as evidenced by the number of users discussing a topic. Spikes in the volume of users typically correspond to external events that increase the public attention on the topic -- as, for instance, discussions about `gun control' often erupt after a mass shooting. This work is the first to study the dynamic evolution of polarized online debates at such scale. By employing a wide array of network and content analysis measures, we find consistent evidence that increased collective attention is associated with increased network polarization and network concentration within each side of the debate; and overall more uniform lexicon usage across all users.Comment: accepted at ACM WebScience 201

Postmortem Analysis of Decayed Online Social Communities: Cascade Pattern Analysis and Prediction

Recently, many online social networks, such as MySpace, Orkut, and Friendster, have faced inactivity decay of their members, which contributed to the collapse of these networks. The reasons, mechanics, and prevention mechanisms of such inactivity decay are not fully understood. In this work, we analyze decayed and alive sub-websites from the StackExchange platform. The analysis mainly focuses on the inactivity cascades that occur among the members of these communities. We provide measures to understand the decay process and statistical analysis to extract the patterns that accompany the inactivity decay. Additionally, we predict cascade size and cascade virality using machine learning. The results of this work include a statistically significant difference of the decay patterns between the decayed and the alive sub-websites. These patterns are mainly: cascade size, cascade virality, cascade duration, and cascade similarity. Additionally, the contributed prediction framework showed satisfactory prediction results compared to a baseline predictor. Supported by empirical evidence, the main findings of this work are: (1) the decay process is not governed by only one network measure; it is better described using multiple measures; (2) the expert members of the StackExchange sub-websites were mainly responsible for the activity or inactivity of the StackExchange sub-websites; (3) the Statistics sub-website is going through decay dynamics that may lead to it becoming fully-decayed; and (4) decayed sub-websites were originally less resilient to inactivity decay, unlike the alive sub-websites

Characterization of ISP Traffic: Trends, User Habits, and Access Technology Impact

In the recent years, the research community has increased its focus on network monitoring which is seen as a key tool to understand the Internet and the Internet users. Several studies have presented a deep characterization of a particular application, or a particular network, considering the point of view of either the ISP, or the Internet user. In this paper, we take a different perspective. We focus on three European countries where we have been collecting traffic for more than a year and a half through 5 vantage points with different access technologies. This humongous amount of information allows us not only to provide precise, multiple, and quantitative measurements of "What the user do with the Internet" in each country but also to identify common/uncommon patterns and habits across different countries and nations. Considering different time scales, we start presenting the trend of application popularity; then we focus our attention to a one-month long period, and further drill into a typical daily characterization of users activity. Results depict an evolving scenario due to the consolidation of new services as Video Streaming and File Hosting and to the adoption of new P2P technologies. Despite the heterogeneity of the users, some common tendencies emerge that can be leveraged by the ISPs to improve their servic

Racial Disparities in Breast Cancer Survival: The Mediating Effects of Macro-Social Context and Social Network Factors

ABSTRACT This study attempts to clarify the associations between macro-social and social network factors and continuing racial disparities in breast cancer survival. The study improves on prior methodologies by using a neighborhood disadvantage measure that assesses both economic and social disadvantage and an ego-network measurement tool that assesses key social network characteristics. Our population-based sample included 786 breast cancer patients (nHWhite=388; nHBlack=398) diagnosed during 2005-2008 in Chicago, IL. The data included census-derived macro-social context, self-reported social network, self-reported demographic and medically abstracted health measures. Mortality data from the National Death Index (NDI) were used to determine 5-year survival. Based on our findings, neighborhood concentrated disadvantage was negatively associated with survival among nHBlack and nHWhite breast cancer patients. In unadjusted models, social network size, network density, practical support, and financial support were positively associated with 5-year survival. However, in adjusted models only practical support was associated with 5-year survival. Our findings suggest that the association between network size and breast cancer survival is sensitive to scaling of the network measure, which helps to explain inconsistencies in past findings. Social networks of nHWhites and nHBlacks differed in size, social support dimensions, network density, and geographic proximity. Among social factors, residence in disadvantaged neighborhoods and unmet practical support explained some of the racial disparity in survival. Differences in late stage diagnosis and comorbidities between nHWhites and nHBlacks also explained some of the racial disparity in survival. Our findings highlight the relevance of social factors, both macro and inter-personal in the racial disparity in breast cancer survival. Findings suggest that reduced survival of nHBlack women is in part due to low social network resources and residence in socially and economically deprived neighborhoods. Our findings indicate that, to improve survival among breast cancer patients, policies need to focus on continued improvement of access to care and reduction of racially patterned social and economic hardship. Additionally, our findings support the need for health care providers to assess social support resources of breast cancer patients at the time of diagnosis

Predicting Empathy From Resting State Brain Connectivity: A Multivariate Approach.

Recent task fMRI studies suggest that individual differences in trait empathy and empathic concern are mediated by patterns of connectivity between self-other resonance and top-down control networks that are stable across task demands. An untested implication of this hypothesis is that these stable patterns of connectivity should be visible even in the absence of empathy tasks. Using machine learning, we demonstrate that patterns of resting state fMRI connectivity (i.e. the degree of synchronous BOLD activity across multiple cortical areas in the absence of explicit task demands) of resonance and control networks predict trait empathic concern (n = 58). Empathic concern was also predicted by connectivity patterns within the somatomotor network. These findings further support the role of resonance-control network interactions and of somatomotor function in our vicariously driven concern for others. Furthermore, a practical implication of these results is that it is possible to assess empathic predispositions in individuals without needing to perform conventional empathy assessments