Results 121 to 130 of about 18,525 (328)
World model inspired sarcasm reasoning with large language model agents
Discover Artificial IntelligenceSarcasm understanding is a challenging problem in natural language processing, as it requires capturing the discrepancy between the surface meaning of an utterance and the speaker’s intentions as well as the surrounding social context.
Keito Inoshita, Shinnosuke Mizuno
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Science Education, EarlyView.ABSTRACT In this article, I examine group science talk within the classrooms of three urban secondary science teachers who regularly use one‐to‐one computers to mediate their NGSS‐aligned science instruction. I combine methods of framing analysis (Goffman 1974; Tannen 1993) and interaction analysis (Jordan and Henderson 1995) to illustrate differences ...
Tess Bernhard
wiley +1 more source
Sustainable Development, EarlyView.ABSTRACT In 2023, The Guardian reported on several scientific studies denouncing the role of certain forest carbon credits in mitigating climate change. Subsequently, credit prices on the voluntary carbon market (VCM) plummeted—providing a quantitative indication of its impact.
Benjamin S. Thompson +3 more
wiley +1 more source
Evidence for Diverse Forms of Sarcasm [PDF]
, 2020 Sarcasm is a difficult concept to define accurately and completely and is similarly hard to identify in natural communication. In three works, this dissertation develops a deeper understanding of sarcasm, both as a concept and as a phenomenon.
D'Arcey, J Trevor
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Detect Sarcasm and Humor Jointly by Neural Multi-Task Learning
IEEE AccessSarcasm is a sophisticated speech act that is intended to express contempt or ridicule on social communities such as Twitter. In recent years, the prevalence of sarcasm on the social media has become highly disruptive to sentiment analysis systems due to
Yufeng Diao +5 more
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TFCD: Towards Multi-modal Sarcasm Detection via Training-Free Counterfactual Debiasing
International Joint Conference on Artificial IntelligenceMulti-modal sarcasm detection (MSD), which aims to identify whether a given sample with multi-modal information (i.e., text and image) is sarcastic, has garnered widespread attention.
Zhi-Hong Zhu +6 more
semanticscholar +1 more source
Economic Anthropology, EarlyView.ABSTRACT In the Chinese kimchi industry, manufacturers employ product names, photographs, and logistical strategies to promote their kimchi's “Koreanness.” So, what makes their kimchi “Korean,” and how does its Koreanness formulate kimchi's commodity value?
Heangjin Park
wiley +1 more source
A Deep Learning Approach for Sarcasm Detection on Twitter [PDF]
International Journal of Information and Communication Technology ResearchSarcasm is a form of speech in which a person expresses his opinion implicitly. We may encounter a seemingly positive sentence in sarcasm, but the speaker has a contrary opinion. Sarcasm can be recognized in spoken language based on body language and the
Mohammad Javad Shayegan, Sara Kojouri
doaj
AI told my cat he's terminally ill
Journal of Hospital Medicine, EarlyView.
Jamila Mammadova
wiley +1 more source
Integrating multimodal data and machine learning for entrepreneurship research
Strategic Entrepreneurship Journal, EarlyView.Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley +1 more source