Results 91 to 100 of about 4,714,839 (322)
A Multi-Task Learning Approach to Sarcasm Detection (Student Abstract)
, 2020 Sarcasm detection plays an important role in natural language processing as it has been considered one of the most challenging subtasks in sentiment analysis and opinion mining applications.
Savini, Edoardo, Caragea, Cornelia
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Uncertainty Quantification for Cardiac Diffusion Tensor Imaging Without Additional Datasets
Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose Cardiac diffusion tensor imaging (cDTI) is subject to physiological noise, thermal noise, and signal corruption, which cause errors in diffusion measures. While a larger dataset can be decimated to investigate the general precision of measures from fitting smaller datasets, uncertainty quantification (UQ) methods for fitting entire ...
Sam Coveney +7 more
wiley +1 more source
Public Administration and Development, EarlyView.ABSTRACT The lack of a common variable for comparison has been a major obstacle to the development of Comparative Public Administration (CPA). State autonomy enables an integrative contextualization approach, allowing both the analysis of contextual individual country experiences and the generation of generalized comparable knowledge.
Wilson Wong
wiley +1 more source
G^2SAM: Graph-Based Global Semantic Awareness Method for Multimodal Sarcasm Detection
AAAI Conference on Artificial IntelligenceMultimodal sarcasm detection, aiming to detect the ironic sentiment within multimodal social data, has gained substantial popularity in both the natural language processing and computer vision communities.
Yiwei Wei +6 more
semanticscholar +1 more source
Public Administration and Development, EarlyView.ABSTRACT Two conceptualizations of pathways to moderating power asymmetries in humanitarian practice have emerged in localization discourse—one emphasizing procedural reforms and the other highlighting relational transformation. Dominant Global North‐mediated localization frameworks emphasize procedural approaches with a focus on shifting to a direct ...
Meghan Sullivan
wiley +1 more source
News Headlines Dataset For Sarcasm Detection
CoRR, 2022 Past studies in Sarcasm Detection mostly make use of Twitter datasets collected using hashtag-based supervision but such datasets are noisy in terms of labels and language. Furthermore, many tweets are replies to other tweets, and detecting sarcasm in these requires the availability of contextual tweets.
openaire +2 more sources
Teachers' Pedagogical Reasoning and Students' Three‐Dimensional Learning
Science Education, EarlyView.ABSTRACT This article reports analyses of data from a design‐based implementation project focused on middle‐ and high‐school science teaching. Drawing on teacher interviews and surveys as well as student learning evidence, we examined the relationships between teachers' pedagogical reasoning and their students' three‐dimensional learning. Most teachers
Christie Morrison Thomas +5 more
wiley +1 more source
SARCASM DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH FINE-TUNING
, 2023 Sarcasm detection is an important task in correctly understanding a sentence. This study proposes a method of sarcasm detection using a Convolutional Neural Network (CNN) with fine-tuning.
大原 虎太郎
core
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
Modified framework for sarcasm detection and classification in sentiment analysis [PDF]
, 2018 Sentiment analysis is directed at identifying people’s opinions, beliefs, views and emotions in the context of the entities and attributes that appear in text. The presence of sarcasm, however, can significantly hamper sentiment analysis. In this paper a
Mohd Suhairi Md Suhaimin +10 more
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