We propose a new theoretical framework for understanding simultaneous trust and distrust within relationships. grounded in assumptions of multidimensionality and the inherent tensions of relationships. and we separate this research from prior work grounded in assumptions of unidimensionality and balance. Drawing foundational support for this new framework from recent research on simultaneous positive and negative sentiments and ambivalence. we explore the theoretical and practical significance of the framework for future work on trust and distrust relationships within organizations.

We propose frameworks and algorithms for identifying communities in social networks that change over time. Communities are intuitively characterized as “unusually densely knit ” subsets of a social network. This notion becomes more problematic if the social interactions change over time. Aggregating social networks over time can radically misrepresent the existing and changing community structure. Instead, we propose an optimization-based approach for modeling dynamic community structure. We prove that finding the most explanatory community structure is NP-hard and APX-hard, and propose algorithms based on dynamic programming, exhaustive search, maximum matching, and greedy heuristics. We demonstrate empirically that the heuristics trace developments of community structure accurately for several synthetic and real-world examples.

A central idea in marketing and diffusion research is that influentials—a minority of individuals who influence an exceptional number of their peers—are important to the formation of public opinion. Here we examine this idea, which we call the “influentials hypothesis,” using a series of computer simulations of interpersonal influence processes. Under most conditions that we consider, we find that large cascades of influence are driven not by influentials, but by a critical mass of easily influenced individuals. Although our results do not exclude the possibility that influentials can be important, they suggest that the influentials hypothesis requires more careful specification and testing than it has received.

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We perform sensitivity analyses to assess the impact of missing data on the structural properties of social networks. The social network is conceived of as being generated by a bipartite graph, in which actors are linked together via multiple interaction contexts or affiliations. We discuss three principal missing data mechanisms: network boundary specification (non-inclusion of actors or affiliations), survey non-response, and censoring by vertex degree (fixed choice design), examining their impact on the scientific collaboration network from the Los Alamos E-print Archive as well as random bipartite graphs. The simulation results show that network boundary specification and fixed choice designs can dramatically alter estimates of network-level statistics. The observed clustering and assortativity coefficients are overestimated via omission of affiliations or fixed choice thereof, and underestimated via actor non-response, which results in inflated measurement error. We also find that social networks with multiple interaction contexts may have certain interesting properties due to the presence of overlapping cliques. In particular, assortativity by degree does not necessarily improve network robustness to random omission of nodes as predicted by current theory.

Public opinion polarization is here conceived as a process of alignment along multiple lines of potential disagreement and measured as growing constraint in individuals ’ preferences. Using NES data from 1972 to 2004, the authors model trends in issue partisanship— the correlation of issue attitudes with party identification—and issue alignment—the correlation between pairs of issues—and find a substantive increase in issue partisanship, but little evidence of issue alignment. The findings suggest that opinion changes correspond more to a resorting of party labels among voters than to greater constraint on issue attitudes: since parties are more polarized, they are now better at sorting individuals along ideological lines. Levels of constraint vary across population subgroups: strong partisans and wealthier and politically sophisticated voters have grown more coherent in their beliefs. The authors discuss the consequences of partisan realignment and group sorting on the political process and potential deviations from the classic pluralistic account of American politics.

We investigate course registration data of 18 semesters at a Korean University to portray the time evolution of students ’ positions in the network of fellow students. Apart from being a study of the social positions of students, the present work is also an example of how large-scale, time resolved, affiliation networks can be analyzed. For example we discuss the proper definitions of weights, and propose a redefined weighted clustering coefficient. Among other things, we find that the students enter the network at the center and are gradually diffusing towards the periphery. On the other hand, the ties to the classmates of the first semester (still present at the university) will, on average, become stronger as time progresses. I.

presently working on a book exploring the same themes as this working paper. In Fall 2005 she was a visiting fellow at the Kellogg Institute.

This article examines the relationship of employee perceptions of information privacy in their work organizations and important psychological and behavioral outcomes. A model is presented in which information privacy predicts psychological empowerment, which in turn predicts discretionary behaviors on the job, including creative performance and organizational citizenship behavior. Results from two studies (Study 1 single organization, N = 310; Study 2 multiple organizations, N = 303) confirm that information privacy entails judgments of information gathering control, information handling control, and legitimacy. Moreover, a model linking information privacy to empowerment, and empowerment to creative performance and OCBs was supported. Findings are discussed in light of organizational attempts to control employees through the gathering and handling of their personal information. Information Privacy in Organizations 3 Information Privacy in Organizations: Empowering Creative and Extra-role Performance Information privacy concerns are growing amongst workers who face increasingly invasive information collection and dissemination demands from their organizations. At the same

This article examines the relationship of employee perceptions of information privacy in their work organizations and important psychological and behavioral outcomes. A model is presented in which information privacy predicts psychological empowerment, which in turn predicts discretionary behaviors on the job, including creative performance and organizational citizenship behavior. Results from two studies (Study 1 single organization, N = 310; Study 2 multiple organizations, N = 303) confirm that information privacy entails judgments of information gathering control, information handling control, and legitimacy. Moreover, a model linking information privacy to empowerment, and empowerment to creative performance and OCBs was supported. Findings are discussed in light of organizational attempts to control employees through the gathering and handling of their personal information. Information Privacy in Organizations 3 Information Privacy in Organizations: Empowering Creative and Extra-role Performance Information privacy concerns are growing amongst workers who face increasingly invasive information collection and dissemination demands from their organizations. At the same time, organizations have an increasing need to monitor and control members who may (either