DeGroot-Based Opinion Formation Under a Global Steering Mechanism
This article investigates how interacting agents arrive to a consensus or a polarized state. We study the opinion formation process under the effect of a global steering mechanism (GSM), which aggregates the opinion-driven stochastic agent states at the network level and feeds back to them a form of...
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Veröffentlicht in: | IEEE transactions on computational social systems 2024-06, Vol.11 (3), p.4040-4057 |
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creator | Conjeaud, Ivan Lorenz-Spreen, Philipp Kalogeratos, Argyris |
description | This article investigates how interacting agents arrive to a consensus or a polarized state. We study the opinion formation process under the effect of a global steering mechanism (GSM), which aggregates the opinion-driven stochastic agent states at the network level and feeds back to them a form of global information. We also propose a new two-layer agent-based opinion formation model, called GSM-DeGroot , that captures the coupled dynamics between agent-to-agent local interactions and the GSM's steering effect. This way, agents are subject to the effects of a DeGroot-like local opinion propagation, as well as to a wide variety of possible aggregated information that can affect their opinions, such as trending news feeds, press coverage, polls, elections, etc. Contrary to the standard DeGroot model, our model allows polarization to emerge by letting agents react to the global information in a stubborn differential way. Moreover, the introduced stochastic agent states produce event stream dynamics that can fit to real event data. We explore numerically the model dynamics to find regimes of qualitatively different behavior. We also challenge our model by fitting it to the dynamics of real topics that attracted the public attention and were recorded on Twitter. Our experiments show that the proposed model holds explanatory power, as it evidently captures real opinion formation dynamics via a relatively small set of interpretable parameters. |
doi_str_mv | 10.1109/TCSS.2023.3330293 |
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We study the opinion formation process under the effect of a global steering mechanism (GSM), which aggregates the opinion-driven stochastic agent states at the network level and feeds back to them a form of global information. We also propose a new two-layer agent-based opinion formation model, called GSM-DeGroot , that captures the coupled dynamics between agent-to-agent local interactions and the GSM's steering effect. This way, agents are subject to the effects of a DeGroot-like local opinion propagation, as well as to a wide variety of possible aggregated information that can affect their opinions, such as trending news feeds, press coverage, polls, elections, etc. Contrary to the standard DeGroot model, our model allows polarization to emerge by letting agents react to the global information in a stubborn differential way. Moreover, the introduced stochastic agent states produce event stream dynamics that can fit to real event data. We explore numerically the model dynamics to find regimes of qualitatively different behavior. We also challenge our model by fitting it to the dynamics of real topics that attracted the public attention and were recorded on Twitter. Our experiments show that the proposed model holds explanatory power, as it evidently captures real opinion formation dynamics via a relatively small set of interpretable parameters.</description><identifier>ISSN: 2329-924X</identifier><identifier>EISSN: 2329-924X</identifier><identifier>EISSN: 2373-7476</identifier><identifier>DOI: 10.1109/TCSS.2023.3330293</identifier><identifier>CODEN: ITCSGL</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Agent-based modeling ; Biological system modeling ; Data models ; DeGroot model ; Dynamics ; event data stream ; Feeds ; global steering ; GSM ; influence ; information aggregation ; mass-movements ; media ; opinion formation dynamics ; Peer-to-peer computing ; polarization ; public debate ; public opinion ; Social networking (online) ; social networks ; Steering mechanisms ; Stochastic processes</subject><ispartof>IEEE transactions on computational social systems, 2024-06, Vol.11 (3), p.4040-4057</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c246t-84e8cfe17b7a95ae99ae1985c36ecffb4c0969684d71c6350750947267801cfc3</cites><orcidid>0000-0001-6319-4154 ; 0009-0003-1544-574X ; 0000-0003-1436-3593</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10380567$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10380567$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Conjeaud, Ivan</creatorcontrib><creatorcontrib>Lorenz-Spreen, Philipp</creatorcontrib><creatorcontrib>Kalogeratos, Argyris</creatorcontrib><title>DeGroot-Based Opinion Formation Under a Global Steering Mechanism</title><title>IEEE transactions on computational social systems</title><addtitle>TCSS</addtitle><description>This article investigates how interacting agents arrive to a consensus or a polarized state. We study the opinion formation process under the effect of a global steering mechanism (GSM), which aggregates the opinion-driven stochastic agent states at the network level and feeds back to them a form of global information. We also propose a new two-layer agent-based opinion formation model, called GSM-DeGroot , that captures the coupled dynamics between agent-to-agent local interactions and the GSM's steering effect. This way, agents are subject to the effects of a DeGroot-like local opinion propagation, as well as to a wide variety of possible aggregated information that can affect their opinions, such as trending news feeds, press coverage, polls, elections, etc. Contrary to the standard DeGroot model, our model allows polarization to emerge by letting agents react to the global information in a stubborn differential way. Moreover, the introduced stochastic agent states produce event stream dynamics that can fit to real event data. We explore numerically the model dynamics to find regimes of qualitatively different behavior. We also challenge our model by fitting it to the dynamics of real topics that attracted the public attention and were recorded on Twitter. Our experiments show that the proposed model holds explanatory power, as it evidently captures real opinion formation dynamics via a relatively small set of interpretable parameters.</description><subject>Agent-based modeling</subject><subject>Biological system modeling</subject><subject>Data models</subject><subject>DeGroot model</subject><subject>Dynamics</subject><subject>event data stream</subject><subject>Feeds</subject><subject>global steering</subject><subject>GSM</subject><subject>influence</subject><subject>information aggregation</subject><subject>mass-movements</subject><subject>media</subject><subject>opinion formation dynamics</subject><subject>Peer-to-peer computing</subject><subject>polarization</subject><subject>public debate</subject><subject>public opinion</subject><subject>Social networking (online)</subject><subject>social networks</subject><subject>Steering mechanisms</subject><subject>Stochastic processes</subject><issn>2329-924X</issn><issn>2329-924X</issn><issn>2373-7476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkE1PAjEURRujiQT5ASYuJnE9-PrdLhEFTTAsgMRdU8obHQJTbIeF_14muGD17uLc-5JDyD2FIaVgn5bjxWLIgPEh5xyY5VekxzizpWXi8_oi35JBzlsAoExKzaBHRi84TTG25bPPuCnmh7qpY1NMYtr7tkurZoOp8MV0F9d-VyxaxFQ3X8UHhm_f1Hl_R24qv8s4-L99spq8Lsdv5Ww-fR-PZmVgQrWlEWhChVSvtbfSo7UeqTUycIWhqtYigFVWGbHRNCguQUuwQjOlDdBQBd4nj-fdQ4o_R8yt28Zjak4vHQdlqBaWmRNFz1RIMeeElTukeu_Tr6PgOlmuk-U6We5f1qnzcO7UiHjBcwNSaf4H1lJkHQ</recordid><startdate>20240601</startdate><enddate>20240601</enddate><creator>Conjeaud, Ivan</creator><creator>Lorenz-Spreen, Philipp</creator><creator>Kalogeratos, Argyris</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-6319-4154</orcidid><orcidid>https://orcid.org/0009-0003-1544-574X</orcidid><orcidid>https://orcid.org/0000-0003-1436-3593</orcidid></search><sort><creationdate>20240601</creationdate><title>DeGroot-Based Opinion Formation Under a Global Steering Mechanism</title><author>Conjeaud, Ivan ; Lorenz-Spreen, Philipp ; Kalogeratos, Argyris</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c246t-84e8cfe17b7a95ae99ae1985c36ecffb4c0969684d71c6350750947267801cfc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Agent-based modeling</topic><topic>Biological system modeling</topic><topic>Data models</topic><topic>DeGroot model</topic><topic>Dynamics</topic><topic>event data stream</topic><topic>Feeds</topic><topic>global steering</topic><topic>GSM</topic><topic>influence</topic><topic>information aggregation</topic><topic>mass-movements</topic><topic>media</topic><topic>opinion formation dynamics</topic><topic>Peer-to-peer computing</topic><topic>polarization</topic><topic>public debate</topic><topic>public opinion</topic><topic>Social networking (online)</topic><topic>social networks</topic><topic>Steering mechanisms</topic><topic>Stochastic processes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Conjeaud, Ivan</creatorcontrib><creatorcontrib>Lorenz-Spreen, Philipp</creatorcontrib><creatorcontrib>Kalogeratos, Argyris</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on computational social systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Conjeaud, Ivan</au><au>Lorenz-Spreen, Philipp</au><au>Kalogeratos, Argyris</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>DeGroot-Based Opinion Formation Under a Global Steering Mechanism</atitle><jtitle>IEEE transactions on computational social systems</jtitle><stitle>TCSS</stitle><date>2024-06-01</date><risdate>2024</risdate><volume>11</volume><issue>3</issue><spage>4040</spage><epage>4057</epage><pages>4040-4057</pages><issn>2329-924X</issn><eissn>2329-924X</eissn><eissn>2373-7476</eissn><coden>ITCSGL</coden><abstract>This article investigates how interacting agents arrive to a consensus or a polarized state. 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We explore numerically the model dynamics to find regimes of qualitatively different behavior. We also challenge our model by fitting it to the dynamics of real topics that attracted the public attention and were recorded on Twitter. Our experiments show that the proposed model holds explanatory power, as it evidently captures real opinion formation dynamics via a relatively small set of interpretable parameters.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/TCSS.2023.3330293</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0001-6319-4154</orcidid><orcidid>https://orcid.org/0009-0003-1544-574X</orcidid><orcidid>https://orcid.org/0000-0003-1436-3593</orcidid></addata></record> |
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subjects | Agent-based modeling Biological system modeling Data models DeGroot model Dynamics event data stream Feeds global steering GSM influence information aggregation mass-movements media opinion formation dynamics Peer-to-peer computing polarization public debate public opinion Social networking (online) social networks Steering mechanisms Stochastic processes |
title | DeGroot-Based Opinion Formation Under a Global Steering Mechanism |
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