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Neural network trained on 'Friends' can recognize sarcasm

Neural network trained on 'Friends' can recognize sarcasm
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United States , Association For Computational Linguistics , Acoustical Society Of America , Canadian Acoustical Association , University Of Michigan , University Of Groningen , Multimodal Sarcasm Detection , Big Bang , Sarcasm Detection Dataset , Acoustical Society ,

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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Carnegie Endowment For International Peace , District Of Columbia , United States , New York , White House , Nairobi Area , Han I , Republic Of , South Africa , Soult Ukpyolsi , South Korea , Andhra Pradesh , United Kingdom , Minh Thuan Nguyen , Nitasha Tiku , Ranjit Singh , Papa Reo , Shivani Kapania , Edel Rodriguez , Neema Iyer , Nithya Sambasivan , Aisingapore Sealion , Angeline Wairegi , Tahu Kukutai , Kevin Schaul , Dylan Patel ,

Advancing a More Global Agenda for Trustworthy Artificial Intelligence

Advancing a More Global Agenda for Trustworthy Artificial Intelligence
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South Africa , White House , District Of Columbia , United States , New York , Andhra Pradesh , Republic Of , Carnegie Endowment For International Peace , Soult Ukpyolsi , South Korea , Nairobi Area , United Kingdom , Han I , Jeanne Whalen , Tevin Tafese , Abhishek Gupta , Tianchong Wang , Szu Yu Chen , Google Tensorflow , Vittoria Elliott , Libing Wang , Indosat Ooredoo Hutchison , Alek Tarkowski , Henry Kronk , Aubra Anthony , Paul Keller ,

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 ....

South Korea , United States , Francisci Morales , Facebook Community Standards , Conference On Online Social Networks , European Language Resources Association , Wh Network , Terms Of Service , How Does Youtube Enforce Its Community Guidelines , Meeting Of The Association For Computational Linguistics , International World Wide Web Conferences Steering Committee , Association For Computational Linguistics , Association For Computing Machinery , Association For The Advancement Of Artificial Intelligence , Social Netw , Media Soc , Wide Web Conference , Human Factors , Computing Systems , Computing Machinery , Science Conference , Language Resources , Evaluation Conference , Social Media , Artificial Intelligence , Knowledge Discovery ,