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

Authors

429

  1. AB
    Alexandra Balahur

    University of Alicante, Spain

    3 publications · 112 citations

    3

    h-index

  2. EB
    Estér Boldrini

    University of Alicante, Spain

    3 publications · 129 citations

    3

    h-index

  3. PM
    Patricio Martínez-Barco

    University of Alicante, Spain

    3 publications · 129 citations

    3

    h-index

  4. RM
    Ryan McDonald

    Google (United States), United States

    3 publications · 1.2K citations

    3

    h-index

  5. IT
    Ivan Titov

    University of Amsterdam, Netherlands

    3 publications · 665 citations

    3

    h-index

1–5 of 429

Venues

  1. Procedia Computer Science

    4 publications · 802 citations

    4

    h-index

  2. IEEE Intelligent Systems

    3 publications · 1.3K citations

    3

    h-index

  3. Expert Systems with Applications

    3 publications · 169 citations

    3

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 178 citations

    3

    h-index

  5. ACM Transactions on the Web

    TWEB · 2 publications · 130 citations

    2

    h-index

1–5