Loading…
Opinion models, data, and politics
We investigate the connection between Potts (Curie-Weiss) models and stochastic opinion models in the view of the Boltzmann distribution and stochastic Glauber dynamics. We particularly find that the q-voter model can be considered as a natural extension of the Zealot model which is adapted by Lagra...
Saved in:
Published in: | arXiv.org 2024-02 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | |
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Gsänger, Matthias Hösel, Volker Mohamad-Klotzbach, Christoph Müller, Johannes |
description | We investigate the connection between Potts (Curie-Weiss) models and stochastic opinion models in the view of the Boltzmann distribution and stochastic Glauber dynamics. We particularly find that the q-voter model can be considered as a natural extension of the Zealot model which is adapted by Lagrangian parameters. We also discuss weak and strong effects continuum limits for the models. We then fit four models (Curie-Weiss, strong and weak effects limit for the q-voter model, and the reinforcement model) to election data from United States, United Kingdom, France and Germany. We find that particularly the weak effects models are able to fit the data (Kolmogorov-Smirnov test), where the weak effects reinforcement model performs best (AIC). The resulting estimates are interpreted in the view of political sciences, and also the importance of this kind of model-based approaches to election data for the political sciences is discussed. |
format | article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2925760516</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2925760516</sourcerecordid><originalsourceid>FETCH-proquest_journals_29257605163</originalsourceid><addsrcrecordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mRQ8i_IzMvMz1PIzU9JzSnWUUhJLEnUUUjMS1EoyM_JLMlMLuZhYE1LzClO5YXS3AzKbq4hzh66BUX5haWpxSXxWfmlRXlAqXgjSyNTczMDU0MzY-JUAQAvxy1p</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2925760516</pqid></control><display><type>article</type><title>Opinion models, data, and politics</title><source>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</source><creator>Gsänger, Matthias ; Hösel, Volker ; Mohamad-Klotzbach, Christoph ; Müller, Johannes</creator><creatorcontrib>Gsänger, Matthias ; Hösel, Volker ; Mohamad-Klotzbach, Christoph ; Müller, Johannes</creatorcontrib><description>We investigate the connection between Potts (Curie-Weiss) models and stochastic opinion models in the view of the Boltzmann distribution and stochastic Glauber dynamics. We particularly find that the q-voter model can be considered as a natural extension of the Zealot model which is adapted by Lagrangian parameters. We also discuss weak and strong effects continuum limits for the models. We then fit four models (Curie-Weiss, strong and weak effects limit for the q-voter model, and the reinforcement model) to election data from United States, United Kingdom, France and Germany. We find that particularly the weak effects models are able to fit the data (Kolmogorov-Smirnov test), where the weak effects reinforcement model performs best (AIC). The resulting estimates are interpreted in the view of political sciences, and also the importance of this kind of model-based approaches to election data for the political sciences is discussed.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Boltzmann distribution ; Elections ; Kolmogorov-Smirnov test ; Voters</subject><ispartof>arXiv.org, 2024-02</ispartof><rights>2024. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2925760516?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>777,781,25734,36993,44571</link.rule.ids></links><search><creatorcontrib>Gsänger, Matthias</creatorcontrib><creatorcontrib>Hösel, Volker</creatorcontrib><creatorcontrib>Mohamad-Klotzbach, Christoph</creatorcontrib><creatorcontrib>Müller, Johannes</creatorcontrib><title>Opinion models, data, and politics</title><title>arXiv.org</title><description>We investigate the connection between Potts (Curie-Weiss) models and stochastic opinion models in the view of the Boltzmann distribution and stochastic Glauber dynamics. We particularly find that the q-voter model can be considered as a natural extension of the Zealot model which is adapted by Lagrangian parameters. We also discuss weak and strong effects continuum limits for the models. We then fit four models (Curie-Weiss, strong and weak effects limit for the q-voter model, and the reinforcement model) to election data from United States, United Kingdom, France and Germany. We find that particularly the weak effects models are able to fit the data (Kolmogorov-Smirnov test), where the weak effects reinforcement model performs best (AIC). The resulting estimates are interpreted in the view of political sciences, and also the importance of this kind of model-based approaches to election data for the political sciences is discussed.</description><subject>Boltzmann distribution</subject><subject>Elections</subject><subject>Kolmogorov-Smirnov test</subject><subject>Voters</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mRQ8i_IzMvMz1PIzU9JzSnWUUhJLEnUUUjMS1EoyM_JLMlMLuZhYE1LzClO5YXS3AzKbq4hzh66BUX5haWpxSXxWfmlRXlAqXgjSyNTczMDU0MzY-JUAQAvxy1p</recordid><startdate>20240210</startdate><enddate>20240210</enddate><creator>Gsänger, Matthias</creator><creator>Hösel, Volker</creator><creator>Mohamad-Klotzbach, Christoph</creator><creator>Müller, Johannes</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20240210</creationdate><title>Opinion models, data, and politics</title><author>Gsänger, Matthias ; Hösel, Volker ; Mohamad-Klotzbach, Christoph ; Müller, Johannes</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_29257605163</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Boltzmann distribution</topic><topic>Elections</topic><topic>Kolmogorov-Smirnov test</topic><topic>Voters</topic><toplevel>online_resources</toplevel><creatorcontrib>Gsänger, Matthias</creatorcontrib><creatorcontrib>Hösel, Volker</creatorcontrib><creatorcontrib>Mohamad-Klotzbach, Christoph</creatorcontrib><creatorcontrib>Müller, Johannes</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gsänger, Matthias</au><au>Hösel, Volker</au><au>Mohamad-Klotzbach, Christoph</au><au>Müller, Johannes</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Opinion models, data, and politics</atitle><jtitle>arXiv.org</jtitle><date>2024-02-10</date><risdate>2024</risdate><eissn>2331-8422</eissn><abstract>We investigate the connection between Potts (Curie-Weiss) models and stochastic opinion models in the view of the Boltzmann distribution and stochastic Glauber dynamics. We particularly find that the q-voter model can be considered as a natural extension of the Zealot model which is adapted by Lagrangian parameters. We also discuss weak and strong effects continuum limits for the models. We then fit four models (Curie-Weiss, strong and weak effects limit for the q-voter model, and the reinforcement model) to election data from United States, United Kingdom, France and Germany. We find that particularly the weak effects models are able to fit the data (Kolmogorov-Smirnov test), where the weak effects reinforcement model performs best (AIC). The resulting estimates are interpreted in the view of political sciences, and also the importance of this kind of model-based approaches to election data for the political sciences is discussed.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2024-02 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2925760516 |
source | Publicly Available Content Database (Proquest) (PQ_SDU_P3) |
subjects | Boltzmann distribution Elections Kolmogorov-Smirnov test Voters |
title | Opinion models, data, and politics |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T13%3A48%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Opinion%20models,%20data,%20and%20politics&rft.jtitle=arXiv.org&rft.au=Gs%C3%A4nger,%20Matthias&rft.date=2024-02-10&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2925760516%3C/proquest%3E%3Cgrp_id%3Ecdi_FETCH-proquest_journals_29257605163%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2925760516&rft_id=info:pmid/&rfr_iscdi=true |