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Neural network trained on 'Friends' can recognize sarcasm

Neural network trained on 'Friends' can recognize sarcasm
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Advancing a More Global Agenda for Trustworthy Artificial Intelligence

Advancing a More Global Agenda for Trustworthy Artificial Intelligence
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Advancing a More Global Agenda for Trustworthy Artificial Intelligence

Advancing a More Global Agenda for Trustworthy Artificial Intelligence
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Advancing a More Global Agenda for Trustworthy Artificial Intelligence

Advancing a More Global Agenda for Trustworthy Artificial Intelligence
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Persistent interaction patterns across social media platforms and over time

Growing concern surrounds the impact of social media platforms on public discourse1–4 and their influence on social dynamics5–9, especially in the context of toxicity10–12. Here, to better understand these phenomena, we use a comparative approach to isolate human behavioural patterns across multiple social media platforms. In particular, we analyse conversations in different online communities, focusing on identifying consistent patterns of toxic content. Drawing from an extensive dataset that spans eight platforms over 34 years—from Usenet to contemporary social media—our findings show consistent conversation patterns and user behaviour, irrespective of the platform, topic or time. Notably, although long conversations consistently exhibit higher toxicity, toxic language does not invariably discourage people from participating in a conversation, and toxicity does not necessarily escalate as discussions evolve. Our analysis suggests that debates and contras ....

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