Data from: Better baboon breakups: collective decision theory of complex social network fissions

2021 ◽  
Author(s):  
Karen C. Abbott ◽  
Brian A Lerch ◽  
Elizabeth A. Archie ◽  
Susan C. Alberts ◽  
L.I. Siodi ◽  
...  
Keyword(s):  
Social Network ◽  
Decision Theory ◽  
Collective Decision

Data from: Better baboon breakups: collective decision theory of complex social network fissions

2021 ◽  
Author(s):  
Elizabeth A. Archie ◽  
Karen C. Abbott ◽  
Susan C. Alberts ◽  
Brian A Lerch ◽  
S.N. Sayialel ◽  
...  
Keyword(s):  
Social Network ◽  
Decision Theory ◽  
Collective Decision

Data from: Better baboon breakups: collective decision theory of complex social network fissions

2021 ◽  
Author(s):  
Brian A Lerch ◽  
Karen C. Abbott ◽  
Susan C. Alberts ◽  
Elizabeth A. Archie ◽  
J.K. Warutere ◽  
...  
Keyword(s):  
Social Network ◽  
Decision Theory ◽  
Collective Decision

scholarly journals Coalitional Strategic Behaviour in Collective Decision Making

2020 ◽  
Vol 34 (10) ◽  
pp. 13722-13723
Author(s):  
Grzegorz Lisowski
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Collective Decision ◽  
Special Focus ◽  
Collective Decision Making ◽  
Strategic Behaviour ◽  
Voting Mechanisms ◽  
Selection Of

In my PhD project I study the algorithmic aspects of strategic behaviour in collective decision making, with the special focus on voting mechanisms. I investigate two manners of manipulation: (1) strategic selection of candidates from groups of potential representatives and (2) influence on voters located in a social network.

scholarly journals Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Shelley D. Dionne ◽  
Hiroki Sayama ◽  
Francis J. Yammarino
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Network Structure ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Theoretic Approach ◽  
Agent Based ◽  
Social Network Structure ◽  
Agent Based Simulations ◽  
Simulation Results

Collective, especially group-based, managerial decision making is crucial in organizations. Using an evolutionary theoretic approach to collective decision making, agent-based simulations were conducted to investigate how human collective decision making would be affected by the agents’ diversity in problem understanding and/or behavior in discussion, as well as by their social network structure. Simulation results indicated that groups with consistent problem understanding tended to produce higher utility values of ideas and displayed better decision convergence, but only if there was no group-level bias in collective problem understanding. Simulation results also indicated the importance of balance between selection-oriented (i.e., exploitative) and variation-oriented (i.e., explorative) behaviors in discussion to achieve quality final decisions. Expanding the group size and introducing nontrivial social network structure generally improved the quality of ideas at the cost of decision convergence. Simulations with different social network topologies revealed collective decision making on small-world networks with high local clustering tended to achieve highest decision quality more often than on random or scale-free networks. Implications of this evolutionary theory and simulation approach for future managerial research on collective, group, and multilevel decision making are discussed.

scholarly journals From Social Network (Centralized vs. Decentralized) to Collective Decision-Making (Unshared vs. Shared Consensus)

PLoS ONE ◽  
2012 ◽  
Vol 7 (2) ◽  
pp. e32566 ◽  
Author(s):  
Cédric Sueur ◽  
Jean-Louis Deneubourg ◽  
Odile Petit
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Collective Decision ◽  
Collective Decision Making

Using Social Network Analysis to Support Collective Decision-Making Process

2013 ◽  
pp. 87-103 ◽  
Author(s):  
Simon Buckingham Shum ◽  
Lorella Cannavacciuolo ◽  
Anna De Liddo ◽  
Luca Iandoli ◽  
Ivana Quinto
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Collective Decision ◽  
Knowledge Organization ◽  
Decision Making Process ◽  
Collective Decision Making ◽  
Collaborative Decision Making ◽  
Collaborative Decision

Current traditional technologies, while enabling effective knowledge sharing and accumulation, seem to be less supportive of knowledge organization, use and consensus formation, as well as of collaborative decision making process. To address these limitations and thus to better foster collective decision-making around complex and controversial problems, a new family of tools is emerging able to support more structured knowledge representations known as collaborative argument mapping tools. This paper argues that online collaborative argumentation has the rather unique feature of combining knowledge organization with social mapping and that such a combination can provide interesting insights on the social processes activated within a collaborative decision making initiative. In particular, the authors investigate how Social Network Analysis can be used for the analysis of the collective argumentation process to study the structural properties of the concepts and social networks emerging from users’ interaction. Using Cohere, an online platform designed to support collaborative argumentation, some empirical findings obtained from two use cases are presented.

Using Social Network Analysis to Support Collective Decision-Making Process

2011 ◽  
Vol 3 (2) ◽  
pp. 15-31 ◽  
Author(s):  
Simon Buckingham Shum ◽  
Lorella Cannavacciuolo ◽  
Anna De Liddo ◽  
Luca Iandoli ◽  
Ivana Quinto
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Collective Decision ◽  
Knowledge Organization ◽  
Decision Making Process ◽  
Collective Decision Making ◽  
Collaborative Decision Making ◽  
Collaborative Decision

Current traditional technologies, while enabling effective knowledge sharing and accumulation, seem to be less supportive of knowledge organization, use and consensus formation, as well as of collaborative decision making process. To address these limitations and thus to better foster collective decision-making around complex and controversial problems, a new family of tools is emerging able to support more structured knowledge representations known as collaborative argument mapping tools. This paper argues that online collaborative argumentation has the rather unique feature of combining knowledge organization with social mapping and that such a combination can provide interesting insights on the social processes activated within a collaborative decision making initiative. In particular, the authors investigate how Social Network Analysis can be used for the analysis of the collective argumentation process to study the structural properties of the concepts and social networks emerging from users’ interaction. Using Cohere, an online platform designed to support collaborative argumentation, some empirical findings obtained from two use cases are presented.

Representation, abstraction, and simple-minded sophisticates

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan
Keyword(s):  
Decision Theory ◽  
Predictive Coding ◽  
Bayesian Decision Theory ◽  
Bayesian Decision ◽  
Model Based ◽  
Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social

Abstract #1249: Novel Use of Physician Social Network Data to Map the Gap in the Endocrinology Workforce

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban
Keyword(s):  
Social Network ◽  
Network Data ◽  
Social Network Data
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