Networks of Mobilization: Student Involvement in a Municipal Election

An enduring issue in the study of political participation is the extent to which political awareness and engagement are socially or individually motivated. We address these issues in the context of a municipal election which generated a high level of political engagement on the part of college students for whom the election was relevant. An effort was made to interview all these students using an on-line survey, and the students were asked to provide information on their friendship networks. The paper demonstrates that awareness and engagement are not simply a consequence of individually defined interests and awareness, but rather that individuals are informed and engaged based on their locations within structured networks of social interaction

The South, the suburbs, and the Vatican too: explaining partisan change among Catholics

This paper explains changes in partisanship among Catholics in the last quarter of the 20th Century using a theory of partisan change centered on the contexts in which Catholics lived. Catholics were part of the post-New Deal Democratic coalition, but they have become a swing demographic group. We argue that these changes in partisanship are best explained by changes in elite messages that are filtered through an individual’s social network. Those Catholics who lived or moved into the increasingly Republican suburbs and South were the Catholics who were most likely to adopt a non-Democratic partisan identity. Changes in context better explain Catholic partisanship than party abortion policy post Roe v. Wade or ideological sorting. We demonstrate evidence in support of our argument using the ANES cumulative file from 1972 through 2000

Opinion Dynamics of Learning Agents: Does Seeking Consensus Lead to Disagreement?

We study opinion dynamics in a population of interacting adaptive agents voting on a set of complex multidimensional issues. We consider agents which can classify issues into for or against. The agents arrive at the opinions about each issue in question using an adaptive algorithm. Adaptation comes from learning and the information for the learning process comes from interacting with other neighboring agents and trying to change the internal state in order to concur with their opinions. The change in the internal state is driven by the information contained in the issue and in the opinion of the other agent. We present results in a simple yet rich context where each agent uses a Boolean Perceptron to state its opinion. If there is no internal clock, so the update occurs with asynchronously exchanged information among pairs of agents, then the typical case, if the number of issues is kept small, is the evolution into a society thorn by the emergence of factions with extreme opposite beliefs. This occurs even when seeking consensus with agents with opposite opinions. The curious result is that it is learning from those that hold the same opinions that drives the emergence of factions. This results follows from the fact that factions are prevented by not learning at all from those agents that hold the same opinion. If the number of issues is large, the dynamics becomes trapped and the society does not evolve into factions and a distribution of moderate opinions is observed. We also study the less realistic, but technically simpler synchronous case showing that global consensus is a fixed point. However, the approach to this consensus is glassy in the limit of large societies if agents adapt even in the case of agreement.Comment: 16 pages, 10 figures, revised versio

Trust reality-mining: evidencing the role of friendship for trust diffusion

Value sensitive design is driven by the motivation of making social and moral values central to the development of ICT systems. Among the most challenging concerns when imparting shared values like accountability, transparency, liberty, fairness and trust into information technology are reliable and comprehensive formal and computational models of those values. This paper, educated by trust theories and models from cognitive science, social sciences and artificial intelligence, proposes a novel stochastic computational model of trust, encapsulating abstractions of human cognitive capabilities and empirically evidenced social interaction patterns. Qualitative and quantitative features of trust are identified, upon which our formal model is phrased. Reality mining methods are used to validate the model based on a real life community dataset. We analyze the time-varying dynamics of the interaction and communication patterns of the community, consider varying types of relationships as well as their symmetry. Social network data analysis shows that our model better fits the evolved friendships compared to a well designed synthetic trust model, which is used as the baseline.</p

Pervasive sensing to model political opinions in face-to-face networks

Exposure and adoption of opinions in social networks are important questions in education, business, and government. We de- scribe a novel application of pervasive computing based on using mobile phone sensors to measure and model the face-to-face interactions and subsequent opinion changes amongst undergraduates, during the 2008 US presidential election campaign. We nd that self-reported political discussants have characteristic interaction patterns and can be predicted from sensor data. Mobile features can be used to estimate unique individ- ual exposure to di erent opinions, and help discover surprising patterns of dynamic homophily related to external political events, such as elec- tion debates and election day. To our knowledge, this is the rst time such dynamic homophily e ects have been measured. Automatically esti- mated exposure explains individual opinions on election day. Finally, we report statistically signi cant di erences in the daily activities of individ- uals that change political opinions versus those that do not, by modeling and discovering dominant activities using topic models. We nd people who decrease their interest in politics are routinely exposed (face-to-face) to friends with little or no interest in politics.U.S. Army Research Laboratory (Cooperative Agreement No. W911NF-09-2-0053)United States. Air Force Office of Scientific Research (Award No. FA9550-10-1-0122)Swiss National Science Foundatio

All in the family: partisan disagreement and electoral mobilization in intimate networks—a spillover experiment

We advance the debate about the impact of political disagreement in social networks on electoral participation by addressing issues of causal inference common in network studies, focusing on voters' most important context of interpersonal influence: the household. We leverage a randomly assigned spillover experiment conducted in the United Kingdom, combined with a detailed database of pretreatment party preferences and public turnout records, to identify social influence within heterogeneous and homogeneous partisan households. Our results show that intrahousehold mobilization effects are larger as a result of campaign contact in heterogeneous than in homogeneous partisan households, and larger still when the partisan intensity of the message is exogenously increased, suggesting discussion rather than behavioral contagion as a mechanism. Our results qualify findings from influential observational studies and suggest that within intimate social networks, negative correlations between political heterogeneity and electoral participation are unlikely to result from political disagreement

So close, yet so far away? the effects of city size, density, and growth on local civic participation

Recent studies in the U.S. context have suggested that political participation is a function of the size and concentration of a city’s population. Most of this research focuses on the idea that there is an optimal size and concentration of population that favors active political participation in terms of a higher propensity to vote in local elections, contact local officials, and attend community meetings. The conventional argument suggests a negative relationship between city size and political participation that is mitigated to some extent by the deeper social interactions generated by increased population density. We extend this research by also investigating the influence of population growth on the broader concept of civic participation. Civic participation is a multidimensional concept that requires the use of a broad set of indicators. We expand the number of measures to gauge civic participation at the local level by including data on the formation of volunteer associations, volunteer fire brigades and not-for-profit organizations as well as voter turnout. We test the hypotheses derived from extant research using aggregate data collected from Portuguese cities and discuss the implications of our findings for the literature on local civic participatio

Non-Disruptive Tactics of Suppression Are Superior in Countering Terrorism, Insurgency, and Financial Panics

BACKGROUND: Suppressing damaging aggregate behaviors such as insurgency, terrorism, and financial panics are important tasks of the state. Each outcome of these aggregate behaviors is an emergent property of a system in which each individual's action depends on a subset of others' actions, given by each individual's network of interactions. Yet there are few explicit comparisons of strategies for suppression, and none that fully incorporate the interdependence of individual behavior. METHODS AND FINDINGS: Here I show that suppression tactics that do not require the removal of individuals from networks of interactions are nearly always more effective than those that do. I find using simulation analysis of a general model of interdependent behavior that the degree to which such less disruptive suppression tactics are superior to more disruptive ones increases in the propensity of individuals to engage in the behavior in question. CONCLUSIONS: Thus, hearts-and-minds approaches are generally more effective than force in counterterrorism and counterinsurgency, and partial insurance is usually a better tactic than gag rules in quelling financial panics. Differences between suppression tactics are greater when individual incentives to support terrorist or insurgent groups, or susceptibilities to financial panic, are higher. These conclusions have utility for policy-makers seeking to end bloody conflicts and prevent financial panics. As the model also applies to mass protest, its conclusions provide insight as well into the likely effects of different suppression strategies undertaken by authoritarian regimes seeking to hold on to power in the face of mass movements seeking to end them

KCNV2-associated retinopathy: genotype–phenotype correlations – KCNV2 study group report 3

BACKGROUND/AIMS: To investigate genotype–phenotype associations in patients withKCNV2retinopathy. METHODS: Review of clinical notes, best-corrected visual acuity (BCVA), molecular variants, electroretinography (ERG) and retinal imaging. Subjects were grouped according to the combination ofKCNV2variants—two loss-of-function (TLOF), two missense (TM) or one of each (MLOF)—and parameters were compared. RESULTS: Ninety-two patients were included. The mean age of onset (mean±SD) in TLOF (n=55), TM (n=23) and MLOF (n=14) groups was 3.51±0.58, 4.07±2.76 and 5.54±3.38 years, respectively. The mean LogMAR BCVA (±SD) at baseline in TLOF, TM and MLOF groups was 0.89±0.25, 0.67±0.38 and 0.81±0.35 for right, and 0.88±0.26, 0.69±0.33 and 0.78±0.33 for left eyes, respectively. The difference in BCVA between groups at baseline was significant in right (p=0.03) and left eyes (p=0.035). Mean outer nuclear layer thickness (±SD) at baseline in TLOF, MLOF and TM groups was 37.07±15.20 µm, 40.67±12.53 and 40.38±18.67, respectively, which was not significantly different (p=0.85). The mean ellipsoid zone width (EZW) loss (±SD) was 2051 µm (±1318) for patients in the TLOF, and 1314 µm (±965) for MLOF. Only one patient in the TM group had EZW loss at presentation. There was considerable overlap in ERG findings, although the largest DA 10 ERG b-waves were associated with TLOF and the smallest with TM variants. CONCLUSIONS: Patients with missense alterations had better BCVA and greater structural integrity. This is important for patient prognostication and counselling, as well as stratification for future gene therapy trials