36,180 research outputs found
Organizational Demography and Individual Careers: Structure, Norms, and Outcomes
[Excerpt] As the terms career choices and opportunity structure suggest, demographic influences on careers operate at multiple levels of analysis: at the individual level, on individuals\u27 perceptions of work environments and career decisions, and at the organization level, on group dynamics and organizational selection processes. However, there are few theories that explicate the processes that bridge these levels. What are the dynamics by which demographic patterns influence an individual\u27s career choices? Similarly, how do individual actions shape the processes of demographic change within organizations? This chapter presents one approach to exploring such questions
The Evolution of Wikipedia's Norm Network
Social norms have traditionally been difficult to quantify. In any particular
society, their sheer number and complex interdependencies often limit a
system-level analysis. One exception is that of the network of norms that
sustain the online Wikipedia community. We study the fifteen-year evolution of
this network using the interconnected set of pages that establish, describe,
and interpret the community's norms. Despite Wikipedia's reputation for
\textit{ad hoc} governance, we find that its normative evolution is highly
conservative. The earliest users create norms that both dominate the network
and persist over time. These core norms govern both content and interpersonal
interactions using abstract principles such as neutrality, verifiability, and
assume good faith. As the network grows, norm neighborhoods decouple
topologically from each other, while increasing in semantic coherence. Taken
together, these results suggest that the evolution of Wikipedia's norm network
is akin to bureaucratic systems that predate the information age.Comment: 22 pages, 9 figures. Matches published version. Data available at
http://bit.ly/wiki_nor
Computational Conflict Research
This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network analysis. Empirical cases range from migration policy framing in North America and street protests in Iran to violence against civilians in Congo and food riots world-wide. Supplementary materials in the book include a comprehensive list of the datasets on conflict and dissent, as well as resources to online repositories where the annotated code and data of individual chapters can be found and where (agent-based) models can be re-produced and altered. These materials are a valuable resource for those wishing to retrace and learn from the analyses described in this volume and adapt and apply them to their own research interests. By bringing together novel research through an international team of scholars from a range of disciplines, Computational Conflict Research pioneers and maps this emerging field. The book will appeal to students, scholars, and anyone interested in the prospects of using computational social sciences to advance our understanding of conflict dynamics
Opinion dynamics: models, extensions and external effects
Recently, social phenomena have received a lot of attention not only from
social scientists, but also from physicists, mathematicians and computer
scientists, in the emerging interdisciplinary field of complex system science.
Opinion dynamics is one of the processes studied, since opinions are the
drivers of human behaviour, and play a crucial role in many global challenges
that our complex world and societies are facing: global financial crises,
global pandemics, growth of cities, urbanisation and migration patterns, and
last but not least important, climate change and environmental sustainability
and protection. Opinion formation is a complex process affected by the
interplay of different elements, including the individual predisposition, the
influence of positive and negative peer interaction (social networks playing a
crucial role in this respect), the information each individual is exposed to,
and many others. Several models inspired from those in use in physics have been
developed to encompass many of these elements, and to allow for the
identification of the mechanisms involved in the opinion formation process and
the understanding of their role, with the practical aim of simulating opinion
formation and spreading under various conditions. These modelling schemes range
from binary simple models such as the voter model, to multi-dimensional
continuous approaches. Here, we provide a review of recent methods, focusing on
models employing both peer interaction and external information, and
emphasising the role that less studied mechanisms, such as disagreement, has in
driving the opinion dynamics. [...]Comment: 42 pages, 6 figure
Societies in the wild: cooperation, norms, and hierarchies
MenciĂłn Internacional en el tĂtulo de doctorThis research has been funded in part by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” through grant PGC2018-098186-B-I00 (BASIC).Programa de Doctorado en IngenierĂa Matemática por la Universidad Carlos III de MadridPresidente: Sandro Meloni.- Secretaria: Francesca Lipari.- Vocal: Giulia Andrighett
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