Loading…
Predictive modeling to study lifestyle politics with Facebook likes
“Lifestyle politics” suggests that political and ideological opinions are strongly connected to our consumption choices, music and food taste, cultural preferences, and other aspects of our daily lives. With the growing political polarization this idea has become all the more relevant to a wide rang...
Saved in:
Published in: | EPJ data science 2021-10, Vol.10 (1), p.50-25, Article 50 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c526t-83c676055fc9cfc2486407207cc297428f11ea6b58e84a67466660f8b20d8a1c3 |
---|---|
cites | cdi_FETCH-LOGICAL-c526t-83c676055fc9cfc2486407207cc297428f11ea6b58e84a67466660f8b20d8a1c3 |
container_end_page | 25 |
container_issue | 1 |
container_start_page | 50 |
container_title | EPJ data science |
container_volume | 10 |
creator | Praet, Stiene Van Aelst, Peter van Erkel, Patrick Van der Veeken, Stephan Martens, David |
description | “Lifestyle politics” suggests that political and ideological opinions are strongly connected to our consumption choices, music and food taste, cultural preferences, and other aspects of our daily lives. With the growing political polarization this idea has become all the more relevant to a wide range of social scientists. Empirical research in this domain, however, is confronted with an impractical challenge; this type of detailed information on people’s lifestyle is very difficult to operationalize, and extremely time consuming and costly to query in a survey. A potential valuable alternative data source to capture these values and lifestyle choices is social media data. In this study, we explore the value of Facebook “like” data to complement traditional survey data to study lifestyle politics. We collect a unique dataset of Facebook likes and survey data of more than 6500 participants in Belgium, a fragmented multi-party system. Based on both types of data, we infer the political and ideological preference of our respondents. The results indicate that non-political Facebook likes are indicative of political preference and are useful to describe voters in terms of common interests, cultural preferences, and lifestyle features. This shows that social media data can be a valuable complement to traditional survey data to study lifestyle politics. |
doi_str_mv | 10.1140/epjds/s13688-021-00305-7 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_1080d3665e8941b2aec38dd645486cd5</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_1080d3665e8941b2aec38dd645486cd5</doaj_id><sourcerecordid>2578530164</sourcerecordid><originalsourceid>FETCH-LOGICAL-c526t-83c676055fc9cfc2486407207cc297428f11ea6b58e84a67466660f8b20d8a1c3</originalsourceid><addsrcrecordid>eNqFkctKAzEUhgdRsNS-w4DrsSf3zFKK1UJBF7oOmSRT006bmkyVvr2xI-rObBLCfzmHryhKBDcIUZi6_dqmaUKES1kBRhUAAVaJs2KEUU0qhLA4__O-LCYprQEAEcwI56Ni9hSd9ab3767cBus6v1uVfShTf7DHsvOtS_2xc-U-dL73JpUfvn8t59q4JoRNFmxcuiouWt0lN_m-x8XL_O559lAtH-8Xs9tlZRjmfSWJ4YIDY62pTWswlZyCwCCMwbWgWLYIOc0bJp2kmgvK84FWNhis1MiQcbEYcm3Qa7WPfqvjUQXt1ekjxJXSMQ_ZOYVAgs0LMidrihqsnSHSWk5ZbjWW5azrIWsfw9shL6nW4RB3eXyFmZCMAOI0q-SgMjGkFF3704pAfRFQJwJqIKAyAXUioES21oM1Zctu5eJvwb_eT-cli9E</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2578530164</pqid></control><display><type>article</type><title>Predictive modeling to study lifestyle politics with Facebook likes</title><source>Springer Nature - SpringerLink Journals - Fully Open Access</source><source>ProQuest - Publicly Available Content Database</source><creator>Praet, Stiene ; Van Aelst, Peter ; van Erkel, Patrick ; Van der Veeken, Stephan ; Martens, David</creator><creatorcontrib>Praet, Stiene ; Van Aelst, Peter ; van Erkel, Patrick ; Van der Veeken, Stephan ; Martens, David</creatorcontrib><description>“Lifestyle politics” suggests that political and ideological opinions are strongly connected to our consumption choices, music and food taste, cultural preferences, and other aspects of our daily lives. With the growing political polarization this idea has become all the more relevant to a wide range of social scientists. Empirical research in this domain, however, is confronted with an impractical challenge; this type of detailed information on people’s lifestyle is very difficult to operationalize, and extremely time consuming and costly to query in a survey. A potential valuable alternative data source to capture these values and lifestyle choices is social media data. In this study, we explore the value of Facebook “like” data to complement traditional survey data to study lifestyle politics. We collect a unique dataset of Facebook likes and survey data of more than 6500 participants in Belgium, a fragmented multi-party system. Based on both types of data, we infer the political and ideological preference of our respondents. The results indicate that non-political Facebook likes are indicative of political preference and are useful to describe voters in terms of common interests, cultural preferences, and lifestyle features. This shows that social media data can be a valuable complement to traditional survey data to study lifestyle politics.</description><identifier>ISSN: 2193-1127</identifier><identifier>EISSN: 2193-1127</identifier><identifier>DOI: 10.1140/epjds/s13688-021-00305-7</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Complexity ; Computer Appl. in Social and Behavioral Sciences ; Computer Science ; Culture ; Data science ; Data-driven Science ; Digital media ; Extreme values ; Facebook likes ; Food consumption ; Food preferences ; Identity ; Ideology ; Lifestyles ; Modeling and Theory Building ; Political polarization ; Political preference ; Politicians ; Politics ; Polls & surveys ; Prediction models ; Predictive modeling ; Preferences ; Regular Article ; Scientists ; Social networks ; Surveys ; Voter behavior ; Voters</subject><ispartof>EPJ data science, 2021-10, Vol.10 (1), p.50-25, Article 50</ispartof><rights>The Author(s) 2021</rights><rights>The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-83c676055fc9cfc2486407207cc297428f11ea6b58e84a67466660f8b20d8a1c3</citedby><cites>FETCH-LOGICAL-c526t-83c676055fc9cfc2486407207cc297428f11ea6b58e84a67466660f8b20d8a1c3</cites><orcidid>0000-0001-8955-4437</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2578530164/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2578530164?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Praet, Stiene</creatorcontrib><creatorcontrib>Van Aelst, Peter</creatorcontrib><creatorcontrib>van Erkel, Patrick</creatorcontrib><creatorcontrib>Van der Veeken, Stephan</creatorcontrib><creatorcontrib>Martens, David</creatorcontrib><title>Predictive modeling to study lifestyle politics with Facebook likes</title><title>EPJ data science</title><addtitle>EPJ Data Sci</addtitle><description>“Lifestyle politics” suggests that political and ideological opinions are strongly connected to our consumption choices, music and food taste, cultural preferences, and other aspects of our daily lives. With the growing political polarization this idea has become all the more relevant to a wide range of social scientists. Empirical research in this domain, however, is confronted with an impractical challenge; this type of detailed information on people’s lifestyle is very difficult to operationalize, and extremely time consuming and costly to query in a survey. A potential valuable alternative data source to capture these values and lifestyle choices is social media data. In this study, we explore the value of Facebook “like” data to complement traditional survey data to study lifestyle politics. We collect a unique dataset of Facebook likes and survey data of more than 6500 participants in Belgium, a fragmented multi-party system. Based on both types of data, we infer the political and ideological preference of our respondents. The results indicate that non-political Facebook likes are indicative of political preference and are useful to describe voters in terms of common interests, cultural preferences, and lifestyle features. This shows that social media data can be a valuable complement to traditional survey data to study lifestyle politics.</description><subject>Complexity</subject><subject>Computer Appl. in Social and Behavioral Sciences</subject><subject>Computer Science</subject><subject>Culture</subject><subject>Data science</subject><subject>Data-driven Science</subject><subject>Digital media</subject><subject>Extreme values</subject><subject>Facebook likes</subject><subject>Food consumption</subject><subject>Food preferences</subject><subject>Identity</subject><subject>Ideology</subject><subject>Lifestyles</subject><subject>Modeling and Theory Building</subject><subject>Political polarization</subject><subject>Political preference</subject><subject>Politicians</subject><subject>Politics</subject><subject>Polls & surveys</subject><subject>Prediction models</subject><subject>Predictive modeling</subject><subject>Preferences</subject><subject>Regular Article</subject><subject>Scientists</subject><subject>Social networks</subject><subject>Surveys</subject><subject>Voter behavior</subject><subject>Voters</subject><issn>2193-1127</issn><issn>2193-1127</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqFkctKAzEUhgdRsNS-w4DrsSf3zFKK1UJBF7oOmSRT006bmkyVvr2xI-rObBLCfzmHryhKBDcIUZi6_dqmaUKES1kBRhUAAVaJs2KEUU0qhLA4__O-LCYprQEAEcwI56Ni9hSd9ab3767cBus6v1uVfShTf7DHsvOtS_2xc-U-dL73JpUfvn8t59q4JoRNFmxcuiouWt0lN_m-x8XL_O559lAtH-8Xs9tlZRjmfSWJ4YIDY62pTWswlZyCwCCMwbWgWLYIOc0bJp2kmgvK84FWNhis1MiQcbEYcm3Qa7WPfqvjUQXt1ekjxJXSMQ_ZOYVAgs0LMidrihqsnSHSWk5ZbjWW5azrIWsfw9shL6nW4RB3eXyFmZCMAOI0q-SgMjGkFF3704pAfRFQJwJqIKAyAXUioES21oM1Zctu5eJvwb_eT-cli9E</recordid><startdate>20211002</startdate><enddate>20211002</enddate><creator>Praet, Stiene</creator><creator>Van Aelst, Peter</creator><creator>van Erkel, Patrick</creator><creator>Van der Veeken, Stephan</creator><creator>Martens, David</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><general>SpringerOpen</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KB.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M7P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8955-4437</orcidid></search><sort><creationdate>20211002</creationdate><title>Predictive modeling to study lifestyle politics with Facebook likes</title><author>Praet, Stiene ; Van Aelst, Peter ; van Erkel, Patrick ; Van der Veeken, Stephan ; Martens, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-83c676055fc9cfc2486407207cc297428f11ea6b58e84a67466660f8b20d8a1c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Complexity</topic><topic>Computer Appl. in Social and Behavioral Sciences</topic><topic>Computer Science</topic><topic>Culture</topic><topic>Data science</topic><topic>Data-driven Science</topic><topic>Digital media</topic><topic>Extreme values</topic><topic>Facebook likes</topic><topic>Food consumption</topic><topic>Food preferences</topic><topic>Identity</topic><topic>Ideology</topic><topic>Lifestyles</topic><topic>Modeling and Theory Building</topic><topic>Political polarization</topic><topic>Political preference</topic><topic>Politicians</topic><topic>Politics</topic><topic>Polls & surveys</topic><topic>Prediction models</topic><topic>Predictive modeling</topic><topic>Preferences</topic><topic>Regular Article</topic><topic>Scientists</topic><topic>Social networks</topic><topic>Surveys</topic><topic>Voter behavior</topic><topic>Voters</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Praet, Stiene</creatorcontrib><creatorcontrib>Van Aelst, Peter</creatorcontrib><creatorcontrib>van Erkel, Patrick</creatorcontrib><creatorcontrib>Van der Veeken, Stephan</creatorcontrib><creatorcontrib>Martens, David</creatorcontrib><collection>SpringerOpen</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer science database</collection><collection>Materials Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agriculture Science Database</collection><collection>ProQuest Biological Science Journals</collection><collection>Engineering Database</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Materials science collection</collection><collection>ProQuest - Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>EPJ data science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Praet, Stiene</au><au>Van Aelst, Peter</au><au>van Erkel, Patrick</au><au>Van der Veeken, Stephan</au><au>Martens, David</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predictive modeling to study lifestyle politics with Facebook likes</atitle><jtitle>EPJ data science</jtitle><stitle>EPJ Data Sci</stitle><date>2021-10-02</date><risdate>2021</risdate><volume>10</volume><issue>1</issue><spage>50</spage><epage>25</epage><pages>50-25</pages><artnum>50</artnum><issn>2193-1127</issn><eissn>2193-1127</eissn><abstract>“Lifestyle politics” suggests that political and ideological opinions are strongly connected to our consumption choices, music and food taste, cultural preferences, and other aspects of our daily lives. With the growing political polarization this idea has become all the more relevant to a wide range of social scientists. Empirical research in this domain, however, is confronted with an impractical challenge; this type of detailed information on people’s lifestyle is very difficult to operationalize, and extremely time consuming and costly to query in a survey. A potential valuable alternative data source to capture these values and lifestyle choices is social media data. In this study, we explore the value of Facebook “like” data to complement traditional survey data to study lifestyle politics. We collect a unique dataset of Facebook likes and survey data of more than 6500 participants in Belgium, a fragmented multi-party system. Based on both types of data, we infer the political and ideological preference of our respondents. The results indicate that non-political Facebook likes are indicative of political preference and are useful to describe voters in terms of common interests, cultural preferences, and lifestyle features. This shows that social media data can be a valuable complement to traditional survey data to study lifestyle politics.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1140/epjds/s13688-021-00305-7</doi><tpages>25</tpages><orcidid>https://orcid.org/0000-0001-8955-4437</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2193-1127 |
ispartof | EPJ data science, 2021-10, Vol.10 (1), p.50-25, Article 50 |
issn | 2193-1127 2193-1127 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_1080d3665e8941b2aec38dd645486cd5 |
source | Springer Nature - SpringerLink Journals - Fully Open Access; ProQuest - Publicly Available Content Database |
subjects | Complexity Computer Appl. in Social and Behavioral Sciences Computer Science Culture Data science Data-driven Science Digital media Extreme values Facebook likes Food consumption Food preferences Identity Ideology Lifestyles Modeling and Theory Building Political polarization Political preference Politicians Politics Polls & surveys Prediction models Predictive modeling Preferences Regular Article Scientists Social networks Surveys Voter behavior Voters |
title | Predictive modeling to study lifestyle politics with Facebook likes |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T12%3A47%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Predictive%20modeling%20to%20study%20lifestyle%20politics%20with%20Facebook%20likes&rft.jtitle=EPJ%20data%20science&rft.au=Praet,%20Stiene&rft.date=2021-10-02&rft.volume=10&rft.issue=1&rft.spage=50&rft.epage=25&rft.pages=50-25&rft.artnum=50&rft.issn=2193-1127&rft.eissn=2193-1127&rft_id=info:doi/10.1140/epjds/s13688-021-00305-7&rft_dat=%3Cproquest_doaj_%3E2578530164%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c526t-83c676055fc9cfc2486407207cc297428f11ea6b58e84a67466660f8b20d8a1c3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2578530164&rft_id=info:pmid/&rfr_iscdi=true |