Queuing for Civility: Regulating Emotions and Reducing Toxicity in Digital Discourse
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866912562566660096 |
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| author | Verma, Akriti Islam, Shama Moghaddam, Valeh Anwar, Adnan |
| author_facet | Verma, Akriti Islam, Shama Moghaddam, Valeh Anwar, Adnan |
| contents | The pervasiveness of online toxicity, including hate speech and trolling, disrupts digital interactions and online well-being. Previous research has mainly focused on post-hoc moderation, overlooking the real-time emotional dynamics of online conversations and the impact of users' emotions on others. This paper presents a graph-based framework to identify the need for emotion regulation within online conversations. This framework promotes self-reflection to manage emotional responses and encourage responsible behaviour in real time. Additionally, a comment queuing mechanism is proposed to address intentional trolls who exploit emotions to inflame conversations. This mechanism introduces a delay in publishing comments, giving users time to self-regulate before further engaging in the conversation and helping maintain emotional balance. Analysis of social media data from Twitter and Reddit demonstrates that the graph-based framework reduced toxicity by 12%, while the comment queuing mechanism decreased the spread of anger by 15%, with only 4% of comments being temporarily held on average. These findings indicate that combining real-time emotion regulation with delayed moderation can significantly improve well-being in online environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_00696 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Queuing for Civility: Regulating Emotions and Reducing Toxicity in Digital Discourse Verma, Akriti Islam, Shama Moghaddam, Valeh Anwar, Adnan Human-Computer Interaction Artificial Intelligence Computers and Society Machine Learning Social and Information Networks The pervasiveness of online toxicity, including hate speech and trolling, disrupts digital interactions and online well-being. Previous research has mainly focused on post-hoc moderation, overlooking the real-time emotional dynamics of online conversations and the impact of users' emotions on others. This paper presents a graph-based framework to identify the need for emotion regulation within online conversations. This framework promotes self-reflection to manage emotional responses and encourage responsible behaviour in real time. Additionally, a comment queuing mechanism is proposed to address intentional trolls who exploit emotions to inflame conversations. This mechanism introduces a delay in publishing comments, giving users time to self-regulate before further engaging in the conversation and helping maintain emotional balance. Analysis of social media data from Twitter and Reddit demonstrates that the graph-based framework reduced toxicity by 12%, while the comment queuing mechanism decreased the spread of anger by 15%, with only 4% of comments being temporarily held on average. These findings indicate that combining real-time emotion regulation with delayed moderation can significantly improve well-being in online environments. |
| title | Queuing for Civility: Regulating Emotions and Reducing Toxicity in Digital Discourse |
| topic | Human-Computer Interaction Artificial Intelligence Computers and Society Machine Learning Social and Information Networks |
| url | https://arxiv.org/abs/2509.00696 |