Opinion dynamics and communication networks
Autor(a) principal: | |
---|---|
Data de Publicação: | 2010 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/18233 |
Resumo: | This paper examines the interplay of opinion exchange dynamics and communication network formation. An opinion formation procedure is introduced which is based on an abstract representation of opinions as k–dimensional bit–strings. Individuals interact if the difference in the opinion strings is below a defined similarity threshold dI . Depending on dI , different behaviour of the population is observed: low values result in a state of highly fragmented opinions and higher values yield consensus. The first contribution of this research is to identify the values of parameters dI and k, such that the transition between fragmented opinions and homogeneity takes place. Then, we look at this transition from two per- spectives: first by studying the group size distribution and second by analysing the communication network that is formed by the interactions that take place during the simulation. The emerging networks are classified by statistical means and we find that non–trivial social structures emerge from simple rules for individual communication. Generating networks allows to compare model outcomes with real–world communication patterns. |
id |
RCAP_1e51592b0c95fab59b41165338356a4b |
---|---|
oai_identifier_str |
oai:repositorio.iscte-iul.pt:10071/18233 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Opinion dynamics and communication networksArtificial societiesCo-evolutionComputational modelsOpinion dynamicsSocial networksThis paper examines the interplay of opinion exchange dynamics and communication network formation. An opinion formation procedure is introduced which is based on an abstract representation of opinions as k–dimensional bit–strings. Individuals interact if the difference in the opinion strings is below a defined similarity threshold dI . Depending on dI , different behaviour of the population is observed: low values result in a state of highly fragmented opinions and higher values yield consensus. The first contribution of this research is to identify the values of parameters dI and k, such that the transition between fragmented opinions and homogeneity takes place. Then, we look at this transition from two per- spectives: first by studying the group size distribution and second by analysing the communication network that is formed by the interactions that take place during the simulation. The emerging networks are classified by statistical means and we find that non–trivial social structures emerge from simple rules for individual communication. Generating networks allows to compare model outcomes with real–world communication patterns.World Scientific Publishing2019-06-19T11:53:03Z2010-01-01T00:00:00Z20102019-06-19T12:52:25Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/18233eng0219-525910.1142/S0219525910002438Banisch, S.AraÚjo, T.Louçã, J.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-07-07T03:28:24Zoai:repositorio.iscte-iul.pt:10071/18233Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-07-07T03:28:24Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Opinion dynamics and communication networks |
title |
Opinion dynamics and communication networks |
spellingShingle |
Opinion dynamics and communication networks Banisch, S. Artificial societies Co-evolution Computational models Opinion dynamics Social networks |
title_short |
Opinion dynamics and communication networks |
title_full |
Opinion dynamics and communication networks |
title_fullStr |
Opinion dynamics and communication networks |
title_full_unstemmed |
Opinion dynamics and communication networks |
title_sort |
Opinion dynamics and communication networks |
author |
Banisch, S. |
author_facet |
Banisch, S. AraÚjo, T. Louçã, J. |
author_role |
author |
author2 |
AraÚjo, T. Louçã, J. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Banisch, S. AraÚjo, T. Louçã, J. |
dc.subject.por.fl_str_mv |
Artificial societies Co-evolution Computational models Opinion dynamics Social networks |
topic |
Artificial societies Co-evolution Computational models Opinion dynamics Social networks |
description |
This paper examines the interplay of opinion exchange dynamics and communication network formation. An opinion formation procedure is introduced which is based on an abstract representation of opinions as k–dimensional bit–strings. Individuals interact if the difference in the opinion strings is below a defined similarity threshold dI . Depending on dI , different behaviour of the population is observed: low values result in a state of highly fragmented opinions and higher values yield consensus. The first contribution of this research is to identify the values of parameters dI and k, such that the transition between fragmented opinions and homogeneity takes place. Then, we look at this transition from two per- spectives: first by studying the group size distribution and second by analysing the communication network that is formed by the interactions that take place during the simulation. The emerging networks are classified by statistical means and we find that non–trivial social structures emerge from simple rules for individual communication. Generating networks allows to compare model outcomes with real–world communication patterns. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-01-01T00:00:00Z 2010 2019-06-19T11:53:03Z 2019-06-19T12:52:25Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/18233 |
url |
http://hdl.handle.net/10071/18233 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0219-5259 10.1142/S0219525910002438 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
World Scientific Publishing |
publisher.none.fl_str_mv |
World Scientific Publishing |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
_version_ |
1817546476789694464 |