extended-abstract

Influence-Based Opinion Diffusion: (Extended Abstract)

Author:

Laurence CholvyAuthors Info & Claims

AAMAS '16: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems

May 2016

Pages 1355 - 1356

Published: 09 May 2016 Publication History

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Abstract

This paper presents a formal model of opinion diffusion in a population of agents by assuming that: (i) opinions are propositional formulas or, equivalently, sets of propositional interpretations; (ii) the population of agents is structured according to a binary relation of influence which relates two agents when one influences the other; (iii) any agent orders its influencers according to the strength of the influence relation; (iv) any agent changes its opinion by merging the opinions of its influencers, from the most influential one to the least; (v) there is a special formula, called integrity constraint which expresses something true in the world and which has to be taken into account by the merging operator.

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Cited By

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Auletta VFerraioli DFionda VGreco GElkind EVeloso MAgmon NTaylor M(2019)Maximizing the Spread of an Opinion when Tertium Datur EstProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331823(1207-1215)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.5555/3306127.3331823
Auletta VFerraioli DGreco G(2018)Reasoning about consensus when opinions diffuse through majority dynamicsProceedings of the 27th International Joint Conference on Artificial Intelligence10.5555/3304415.3304424(49-55)Online publication date: 13-Jul-2018
https://dl.acm.org/doi/10.5555/3304415.3304424
Gadek GPauchet AMalandain NKhelif KVercouter LBrunessaux SSheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)Measures for topical cohesion of user communities on TwitterProceedings of the International Conference on Web Intelligence10.1145/3106426.3106467(211-218)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106467
Show More Cited By

Index Terms

Influence-Based Opinion Diffusion: (Extended Abstract)
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems

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Published In

AAMAS '16: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems

May 2016

1580 pages

ISBN:9781450342391

General Chairs:
Catholijn M. Jonker
TU Delft, Netherlands
,
Stacy Marsella
University of Southern California, USA
,
Program Chairs:
John Thangarajah
RMIT University. Australia
,
Karl Tuyls
University of Liverpool, UK

In-Cooperation

SIGAI: ACM Special Interest Group on Artificial Intelligence

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 09 May 2016

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Extended-abstract

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AAMAS '16

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AAMAS '16: International Conference on Agents and Multiagent Systems

May 9 - 13, 2016

Singapore, Singapore

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AAMAS '16 Paper Acceptance Rate 137 of 550 submissions, 25%;

Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

View all

Auletta VFerraioli DFionda VGreco GElkind EVeloso MAgmon NTaylor M(2019)Maximizing the Spread of an Opinion when Tertium Datur EstProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331823(1207-1215)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.5555/3306127.3331823
Auletta VFerraioli DGreco G(2018)Reasoning about consensus when opinions diffuse through majority dynamicsProceedings of the 27th International Joint Conference on Artificial Intelligence10.5555/3304415.3304424(49-55)Online publication date: 13-Jul-2018
https://dl.acm.org/doi/10.5555/3304415.3304424
Gadek GPauchet AMalandain NKhelif KVercouter LBrunessaux SSheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)Measures for topical cohesion of user communities on TwitterProceedings of the International Conference on Web Intelligence10.1145/3106426.3106467(211-218)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106467
Gadek GPauchet AMalandain NKhelif KVercouter LBrunessaux S(2017)Topical cohesion of communities on TwitterProcedia Computer Science10.1016/j.procs.2017.08.171112:C(584-593)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.procs.2017.08.171

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