Ordinal Sentiment Classification
Ordinal Sentiment Classification is a type of sentiment classification task in natural language processing that categorizes text into sentiment labels arranged in a meaningful order, such as star ratings or emotion intensity levels, where the ordinal relationship between classes must be preserved during prediction.
14
Publications
1.8K
Citations
42
Authors
24
Institutions
Publications per year
2017–2026
6
Parents
14
SemEval-2018 Task 1: Affect in Tweets
Saif M. Mohammad, Felipe Bravo-Márquez, Mohammad Salameh et al. · 2018 · 745 citations · Full text
Computing, Data Science, Spanish +17
SemEval-2016 Task 4: Sentiment Analysis in Twitter
Preslav Nakov, Alan Ritter, Sara Rosenthal et al. · 2016 · 435 citations · Full text
Compositional Matrix-Space Models for Sentiment Analysis
Ainur Yessenalina, Claire Cardie · 2011 · 164 citations
Seeing Stars of Valence and Arousal in Blog Posts
IEEE Transactions on Affective Computing · 2013 · 111 citations
Computing, Data Science, Psychology +17
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Hamad bin Khalifa University
Doha, Qatar
2 h-index
5 publications
948 citations
University of Illinois Urbana-Champaign
Urbana, United States
1 h-index
1 publications
16 citations
Nanyang Technological University
Singapore, Singapore
1 h-index
3 publications
135 citations

University of Wolverhampton
Wolverhampton, United Kingdom
1 h-index
1 publications
111 citations
DSO National Laboratories
Singapore, Singapore
1 h-index
5 publications
140 citations

Cornell University
Ithaca, United States
1 h-index
2 publications
328 citations
University of Technology Malaysia
Johor Bahru, Malaysia
1 h-index
3 publications
213 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
1 h-index
2 publications
26 citations
1–8 of 24
1 publications · 45 citations
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Conference · 1 publications · 28 citations
1
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1 publications · 71 citations
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TAC · 1 publications · 111 citations
1
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Repository · 1 publications · 39 citations
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1–5