Negative expressions are shared more on Twitter for public figures than for ordinary users
Social media users tend to produce content that contains more positive than negative emotional language. However, negative emotional language is more likely to be shared. To understand why, research has thus far focused on psychological processes associated with tweets' content. In the current...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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Oxford University Press
2023
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| _version_ | 1826311010039889920 |
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| author | Schone, J Garcia, D Parkinson, B Goldenberg, A |
| author_facet | Schone, J Garcia, D Parkinson, B Goldenberg, A |
| author_sort | Schone, J |
| collection | OXFORD |
| description | Social media users tend to produce content that contains more positive than negative emotional language. However, negative emotional language is more likely to be shared. To understand why, research has thus far focused on psychological processes associated with tweets' content. In the current study, we investigate if the content producer influences the extent to which their negative content is shared. More specifically, we focus on a group of users that are central to the diffusion of content on social media—public figures. We found that an increase in negativity was associated with a stronger increase in sharing for public figures compared to ordinary users. This effect was explained by two user characteristics, the number of followers and thus the strength of ties and the proportion of political tweets. The results shed light on whose negativity is most viral, allowing future research to develop interventions aimed at mitigating overexposure to negative content. |
| first_indexed | 2024-03-07T08:02:05Z |
| format | Journal article |
| id | oxford-uuid:6a059ee1-ca04-476b-b9ed-8bbcd4f297f0 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T08:02:05Z |
| publishDate | 2023 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | oxford-uuid:6a059ee1-ca04-476b-b9ed-8bbcd4f297f02023-10-11T10:14:26ZNegative expressions are shared more on Twitter for public figures than for ordinary usersJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:6a059ee1-ca04-476b-b9ed-8bbcd4f297f0EnglishSymplectic Elements Oxford University Press2023Schone, JGarcia, DParkinson, BGoldenberg, ASocial media users tend to produce content that contains more positive than negative emotional language. However, negative emotional language is more likely to be shared. To understand why, research has thus far focused on psychological processes associated with tweets' content. In the current study, we investigate if the content producer influences the extent to which their negative content is shared. More specifically, we focus on a group of users that are central to the diffusion of content on social media—public figures. We found that an increase in negativity was associated with a stronger increase in sharing for public figures compared to ordinary users. This effect was explained by two user characteristics, the number of followers and thus the strength of ties and the proportion of political tweets. The results shed light on whose negativity is most viral, allowing future research to develop interventions aimed at mitigating overexposure to negative content. |
| spellingShingle | Schone, J Garcia, D Parkinson, B Goldenberg, A Negative expressions are shared more on Twitter for public figures than for ordinary users |
| title | Negative expressions are shared more on Twitter for public figures than for ordinary users |
| title_full | Negative expressions are shared more on Twitter for public figures than for ordinary users |
| title_fullStr | Negative expressions are shared more on Twitter for public figures than for ordinary users |
| title_full_unstemmed | Negative expressions are shared more on Twitter for public figures than for ordinary users |
| title_short | Negative expressions are shared more on Twitter for public figures than for ordinary users |
| title_sort | negative expressions are shared more on twitter for public figures than for ordinary users |
| work_keys_str_mv | AT schonej negativeexpressionsaresharedmoreontwitterforpublicfiguresthanforordinaryusers AT garciad negativeexpressionsaresharedmoreontwitterforpublicfiguresthanforordinaryusers AT parkinsonb negativeexpressionsaresharedmoreontwitterforpublicfiguresthanforordinaryusers AT goldenberga negativeexpressionsaresharedmoreontwitterforpublicfiguresthanforordinaryusers |