Fine-Grained Sentiment Analysis is a subtask of sentiment analysis that classifies text into highly specific sentiment categories—such as very positive, positive, neutral, negative, and very negative—rather than broad polarity labels, thereby enabling a more nuanced understanding of sentiment intensity and orientation.
274
Publications
28K
Citations
945
Authors
327
Institutions
Publications per year
2017–2026
194
Parents
Publications
274
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Richard Socher, Alex Perelygin, Jean Y. Wu et al. · 2013 · 6.8K citations · Full text
Semantic Compositionality through Recursive Matrix-Vector Spaces
Richard Socher, Brody Huval, Christopher D. Manning et al. · 2012 · 1.3K citations
1–5 of 274
Authors
945
- RK
5
h-index
- PB
5
h-index
- LB
4
h-index
- SC
4
h-index
- BJ
4
h-index
1–5 of 945
Institutions
327
Nanyang Technological University
Singapore, Singapore
7 h-index
17 publications
2K citations
Tsinghua University
Beijing, China
6 h-index
21 publications
1.2K citations
Chinese Academy of Sciences
Beijing, China
6 h-index
18 publications
752 citations
Columbia University
New York, United States
5 h-index
5 publications
369 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
5 h-index
10 publications
2.5K citations
Baruch College
New York, United States
4 h-index
4 publications
209 citations
Wuhan University
Wuhan, China
4 h-index
20 publications
652 citations
Peking University
Beijing, China
4 h-index
21 publications
2.2K citations
1–8 of 327
Venues
- arXiv (Cornell University)
Repository · 21 publications · 1.3K citations
18
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- IEEE Access
15 publications · 913 citations
15
h-index
- Knowledge-Based Systems
8 publications · 729 citations
8
h-index
- IEEE/ACM Transactions on Audio Speech and Language Processing
TASLP · 5 publications · 413 citations
5
h-index
- Information Processing & Management
4 publications · 373 citations
4
h-index
1–5