Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo
The echo chamber effect on social media has attracted attention due to its potentially disruptive consequences on society. This study presents a framework to evaluate the impact of personality traits on the formation of echo chambers. Using Weibo and Twitter as platforms, we first define an echo cha...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Psychology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1323117/full |
| _version_ | 1797321053021667328 |
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| author | Xiaolei Song Siliang Guo Siliang Guo Yichang Gao |
| author_facet | Xiaolei Song Siliang Guo Siliang Guo Yichang Gao |
| author_sort | Xiaolei Song |
| collection | DOAJ |
| description | The echo chamber effect on social media has attracted attention due to its potentially disruptive consequences on society. This study presents a framework to evaluate the impact of personality traits on the formation of echo chambers. Using Weibo and Twitter as platforms, we first define an echo chamber as a network where users interact solely with those sharing their opinions, and quantify echo chamber effects through selective exposure and homophily. We then employ an unsupervised personality recognition method to assign a personality model to each user, and compare the distribution differences of echo chambers and personality traits across platforms and topics. Our findings show that, although user personality trait models exhibit similar distributions between topics, differences exist between platforms. Among 243 personality model combinations, over 20% of Weibo echo chamber members are “ynynn” models, while over 15% of Twitter echo chamber members are “nnnny” models. This indicates significant differences in personality traits among echo chamber members between platforms. Specific personality traits attract like-minded individuals to engage in discussions on particular topics, ultimately forming homogeneous communities. These insights are valuable for developing targeted management strategies to prevent the spread of fake news or rumors. |
| first_indexed | 2024-03-08T04:51:57Z |
| format | Article |
| id | doaj.art-c0c9e20817c040a7848dc25a94d5a868 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-03-08T04:51:57Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-c0c9e20817c040a7848dc25a94d5a8682024-02-08T04:55:58ZengFrontiers Media S.A.Frontiers in Psychology1664-10782024-02-011510.3389/fpsyg.2024.13231171323117Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and WeiboXiaolei Song0Siliang Guo1Siliang Guo2Yichang Gao3School of Pre-school Education, Qilu Normal University, Jinan, ChinaSchool of Economics and Management, Qilu Normal University, Jinan, ChinaSchool of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, ChinaCommonwealth Scientific and Industrial Research Organisation (CSIRO), Brisbane, QLD, AustraliaThe echo chamber effect on social media has attracted attention due to its potentially disruptive consequences on society. This study presents a framework to evaluate the impact of personality traits on the formation of echo chambers. Using Weibo and Twitter as platforms, we first define an echo chamber as a network where users interact solely with those sharing their opinions, and quantify echo chamber effects through selective exposure and homophily. We then employ an unsupervised personality recognition method to assign a personality model to each user, and compare the distribution differences of echo chambers and personality traits across platforms and topics. Our findings show that, although user personality trait models exhibit similar distributions between topics, differences exist between platforms. Among 243 personality model combinations, over 20% of Weibo echo chamber members are “ynynn” models, while over 15% of Twitter echo chamber members are “nnnny” models. This indicates significant differences in personality traits among echo chamber members between platforms. Specific personality traits attract like-minded individuals to engage in discussions on particular topics, ultimately forming homogeneous communities. These insights are valuable for developing targeted management strategies to prevent the spread of fake news or rumors.https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1323117/fullpersonality traitsEcho chambersocial mediagroup user characteristicsTwitterWeibo |
| spellingShingle | Xiaolei Song Siliang Guo Siliang Guo Yichang Gao Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo Frontiers in Psychology personality traits Echo chamber social media group user characteristics |
| title | Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo |
| title_full | Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo |
| title_fullStr | Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo |
| title_full_unstemmed | Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo |
| title_short | Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo |
| title_sort | personality traits and their influence on echo chamber formation in social media a comparative study of twitter and weibo |
| topic | personality traits Echo chamber social media group user characteristics |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1323117/full |
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