Uncovering gender stereotypes in controversial science discourse: evidence from computational text and visual analyses across digital platforms
Abstract This study examines how gender stereotypes are reflected in discourses around controversial science issues across two platforms, YouTube and TikTok. Utilizing the Social Identity Model of Deindividuation Effects, we developed hypotheses and research questions about how content creators migh...
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Veröffentlicht in: | Journal of computer-mediated communication 2024-01, Vol.29 (1) |
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description | Abstract
This study examines how gender stereotypes are reflected in discourses around controversial science issues across two platforms, YouTube and TikTok. Utilizing the Social Identity Model of Deindividuation Effects, we developed hypotheses and research questions about how content creators might use gender-related stereotypes to engage audiences. Our analyses of climate change and vaccination videos, considering various modalities such as captions and thumbnails, revealed that themes related to children and health often appeared in videos mentioning women, while science misinformation was more common in videos mentioning men. We observed cross-platform differences in portraying gender stereotypes. YouTube’s video descriptions often highlighted women-associated moral language, whereas TikTok emphasized men-associated moral language. YouTube’s thumbnails frequently featured climate activists or women with nature, while TikTok’s thumbnails showed women in Vlog-style selfies and with feminine gestures. These findings advance understanding about gender and science through a cross-platform, multi-modal approach and offer potential intervention strategies.
Lay Summary
This study explores the use of gender cues and stereotypes in digital science communication on two platforms, YouTube and TikTok, focusing on climate change and vaccination. We observed that on both platforms, women are often associated with themes related to children and health, while men are often mentioned with themes related to conspiracy and misinformation discourses. Notably, gender stereotypes differ across platforms. YouTube’s video descriptions tend to emphasize moral language associated with women, such as care, fairness, and loyalties, whereas TikTok’s video descriptions highlight moral language associated with men, such as authority. Visual differences were also found across platforms. YouTube thumbnails often depict women in nature sceneries or as women scientists and activists. TikTok thumbnails tend to feature women in Vlog-style selfies and with feminine gestures. Our findings offer insights and implications for developing strategies to alleviate gender stereotypes in digital science discussions. |
doi_str_mv | 10.1093/jcmc/zmad052 |
format | Article |
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This study examines how gender stereotypes are reflected in discourses around controversial science issues across two platforms, YouTube and TikTok. Utilizing the Social Identity Model of Deindividuation Effects, we developed hypotheses and research questions about how content creators might use gender-related stereotypes to engage audiences. Our analyses of climate change and vaccination videos, considering various modalities such as captions and thumbnails, revealed that themes related to children and health often appeared in videos mentioning women, while science misinformation was more common in videos mentioning men. We observed cross-platform differences in portraying gender stereotypes. YouTube’s video descriptions often highlighted women-associated moral language, whereas TikTok emphasized men-associated moral language. YouTube’s thumbnails frequently featured climate activists or women with nature, while TikTok’s thumbnails showed women in Vlog-style selfies and with feminine gestures. These findings advance understanding about gender and science through a cross-platform, multi-modal approach and offer potential intervention strategies.
Lay Summary
This study explores the use of gender cues and stereotypes in digital science communication on two platforms, YouTube and TikTok, focusing on climate change and vaccination. We observed that on both platforms, women are often associated with themes related to children and health, while men are often mentioned with themes related to conspiracy and misinformation discourses. Notably, gender stereotypes differ across platforms. YouTube’s video descriptions tend to emphasize moral language associated with women, such as care, fairness, and loyalties, whereas TikTok’s video descriptions highlight moral language associated with men, such as authority. Visual differences were also found across platforms. YouTube thumbnails often depict women in nature sceneries or as women scientists and activists. TikTok thumbnails tend to feature women in Vlog-style selfies and with feminine gestures. Our findings offer insights and implications for developing strategies to alleviate gender stereotypes in digital science discussions.</description><identifier>ISSN: 1083-6101</identifier><identifier>EISSN: 1083-6101</identifier><identifier>DOI: 10.1093/jcmc/zmad052</identifier><language>eng</language><publisher>Hoboken: Oxford University Press</publisher><subject>Men ; Video ; Visual effects ; Visual observation ; Women</subject><ispartof>Journal of computer-mediated communication, 2024-01, Vol.29 (1)</ispartof><rights>The Author(s) 2024. Published by Oxford University Press on behalf of International Communication Association. 2024</rights><rights>The Author(s) 2024. Published by Oxford University Press on behalf of International Communication Association.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c290t-7cbc5a5da5dea681bc2a423be1e98f2d5167d71622959fadbf694b95279f0d473</cites><orcidid>0000-0002-5864-5333 ; 0000-0001-7369-657X ; 0000-0001-5861-728X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,1598,27901,27902</link.rule.ids></links><search><creatorcontrib>Chen, Kaiping</creatorcontrib><creatorcontrib>Duan, Zening</creatorcontrib><creatorcontrib>Kim, Sang Jung</creatorcontrib><title>Uncovering gender stereotypes in controversial science discourse: evidence from computational text and visual analyses across digital platforms</title><title>Journal of computer-mediated communication</title><description>Abstract
This study examines how gender stereotypes are reflected in discourses around controversial science issues across two platforms, YouTube and TikTok. Utilizing the Social Identity Model of Deindividuation Effects, we developed hypotheses and research questions about how content creators might use gender-related stereotypes to engage audiences. Our analyses of climate change and vaccination videos, considering various modalities such as captions and thumbnails, revealed that themes related to children and health often appeared in videos mentioning women, while science misinformation was more common in videos mentioning men. We observed cross-platform differences in portraying gender stereotypes. YouTube’s video descriptions often highlighted women-associated moral language, whereas TikTok emphasized men-associated moral language. YouTube’s thumbnails frequently featured climate activists or women with nature, while TikTok’s thumbnails showed women in Vlog-style selfies and with feminine gestures. These findings advance understanding about gender and science through a cross-platform, multi-modal approach and offer potential intervention strategies.
Lay Summary
This study explores the use of gender cues and stereotypes in digital science communication on two platforms, YouTube and TikTok, focusing on climate change and vaccination. We observed that on both platforms, women are often associated with themes related to children and health, while men are often mentioned with themes related to conspiracy and misinformation discourses. Notably, gender stereotypes differ across platforms. YouTube’s video descriptions tend to emphasize moral language associated with women, such as care, fairness, and loyalties, whereas TikTok’s video descriptions highlight moral language associated with men, such as authority. Visual differences were also found across platforms. YouTube thumbnails often depict women in nature sceneries or as women scientists and activists. TikTok thumbnails tend to feature women in Vlog-style selfies and with feminine gestures. Our findings offer insights and implications for developing strategies to alleviate gender stereotypes in digital science discussions.</description><subject>Men</subject><subject>Video</subject><subject>Visual effects</subject><subject>Visual observation</subject><subject>Women</subject><issn>1083-6101</issn><issn>1083-6101</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNp9kE1LAzEQhoMoWKs3f0DAgxfXJtnuR7xJ8QsKXux5ySaTktJN1iRbrH_Cv2z6cfAkDMzMy8PLzIvQNSX3lPB8spKdnHx3QpGCnaARJXWelZTQ0z_zOboIYUUIy1lZj9DPwkq3AW_sEi_BKvA4RPDg4raHgI3F0tnod0gwYo2DNGAlYGWCdIMP8IBhY9Re0951Ce_6IYponE14hK-IhVV4Y8KQdpHEbUjGQnoXQrJZmpj0fi2idr4Ll-hMi3WAq2Mfo8Xz08fsNZu_v7zNHueZZJzErJKtLEShUoEoa9pKJqYsb4ECrzVTBS0rVdGSMV5wLVSrSz5tecEqromaVvkY3Rx8e-8-BwixWaV30nWhySmrUzw8nybq7kDtr_Wgm96bTvhtQ0mzi7zZRd4cI0_47QF3Q_8_-QstB4hK</recordid><startdate>20240101</startdate><enddate>20240101</enddate><creator>Chen, Kaiping</creator><creator>Duan, Zening</creator><creator>Kim, Sang Jung</creator><general>Oxford University Press</general><scope>TOX</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/0000-0002-5864-5333</orcidid><orcidid>https://orcid.org/0000-0001-7369-657X</orcidid><orcidid>https://orcid.org/0000-0001-5861-728X</orcidid></search><sort><creationdate>20240101</creationdate><title>Uncovering gender stereotypes in controversial science discourse: evidence from computational text and visual analyses across digital platforms</title><author>Chen, Kaiping ; Duan, Zening ; Kim, Sang Jung</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c290t-7cbc5a5da5dea681bc2a423be1e98f2d5167d71622959fadbf694b95279f0d473</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Men</topic><topic>Video</topic><topic>Visual effects</topic><topic>Visual observation</topic><topic>Women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Kaiping</creatorcontrib><creatorcontrib>Duan, Zening</creatorcontrib><creatorcontrib>Kim, Sang Jung</creatorcontrib><collection>Oxford Open</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>Journal of computer-mediated communication</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Kaiping</au><au>Duan, Zening</au><au>Kim, Sang Jung</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Uncovering gender stereotypes in controversial science discourse: evidence from computational text and visual analyses across digital platforms</atitle><jtitle>Journal of computer-mediated communication</jtitle><date>2024-01-01</date><risdate>2024</risdate><volume>29</volume><issue>1</issue><issn>1083-6101</issn><eissn>1083-6101</eissn><abstract>Abstract
This study examines how gender stereotypes are reflected in discourses around controversial science issues across two platforms, YouTube and TikTok. Utilizing the Social Identity Model of Deindividuation Effects, we developed hypotheses and research questions about how content creators might use gender-related stereotypes to engage audiences. Our analyses of climate change and vaccination videos, considering various modalities such as captions and thumbnails, revealed that themes related to children and health often appeared in videos mentioning women, while science misinformation was more common in videos mentioning men. We observed cross-platform differences in portraying gender stereotypes. YouTube’s video descriptions often highlighted women-associated moral language, whereas TikTok emphasized men-associated moral language. YouTube’s thumbnails frequently featured climate activists or women with nature, while TikTok’s thumbnails showed women in Vlog-style selfies and with feminine gestures. These findings advance understanding about gender and science through a cross-platform, multi-modal approach and offer potential intervention strategies.
Lay Summary
This study explores the use of gender cues and stereotypes in digital science communication on two platforms, YouTube and TikTok, focusing on climate change and vaccination. We observed that on both platforms, women are often associated with themes related to children and health, while men are often mentioned with themes related to conspiracy and misinformation discourses. Notably, gender stereotypes differ across platforms. YouTube’s video descriptions tend to emphasize moral language associated with women, such as care, fairness, and loyalties, whereas TikTok’s video descriptions highlight moral language associated with men, such as authority. Visual differences were also found across platforms. YouTube thumbnails often depict women in nature sceneries or as women scientists and activists. TikTok thumbnails tend to feature women in Vlog-style selfies and with feminine gestures. Our findings offer insights and implications for developing strategies to alleviate gender stereotypes in digital science discussions.</abstract><cop>Hoboken</cop><pub>Oxford University Press</pub><doi>10.1093/jcmc/zmad052</doi><orcidid>https://orcid.org/0000-0002-5864-5333</orcidid><orcidid>https://orcid.org/0000-0001-7369-657X</orcidid><orcidid>https://orcid.org/0000-0001-5861-728X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Men Video Visual effects Visual observation Women |
title | Uncovering gender stereotypes in controversial science discourse: evidence from computational text and visual analyses across digital platforms |
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