Sentiment Summarization
Sentiment Summarization is a computational method that belongs to the class of sentiment analysis techniques, specifically distinguished by its function of condensing subjectively expressed opinions across multiple texts into a coherent, high-level summary that preserves the dominant sentiments and their nuances.
137
Publications
12.1K
Citations
429
Authors
172
Institutions
Publications per year
2017–2026
64
Parents
137
New Avenues in Opinion Mining and Sentiment Analysis
Erik Cambria, Björn W. Schuller, Yunqing Xia et al. · IEEE Intelligent Systems · 2013 · 1.3K citations
Computing, Computer Science, Natural Language Processing +16
Tetsuya Nasukawa, Jeonghee Yi · 2003 · 1.2K citations
The Role of Text Pre-processing in Sentiment Analysis
E. Haddi, Xiaohui Liu, Yong Shi · Procedia Computer Science · 2013 · 612 citations · Full text
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Tsinghua University
Beijing, China
4 h-index
11 publications
1.8K citations
Google (United States)
Mountain View, United States
4 h-index
9 publications
2.9K citations

University of Alicante
Alicante, Spain
3 h-index
15 publications
570 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
5 publications
471 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
5 publications
702 citations
Indian Institute of Technology Kharagpur
Kharagpur, India
2 h-index
9 publications
1.3K citations
University of Illinois Chicago
Chicago, United States
2 h-index
2 publications
142 citations
Technical University of Munich
Munich, Germany
2 h-index
3 publications
1.5K citations
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4 publications · 802 citations
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3 publications · 1.3K citations
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3 publications · 169 citations
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Conference · 3 publications · 178 citations
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TWEB · 2 publications · 130 citations
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