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

Authors

42

  1. JW
    Junhui Wang

    University of Illinois Chicago, United States

    1 publications · 16 citations

    1

    h-index

  2. YZ
    You Zhang

    Yunnan University, China

    1 publications · 36 citations

    1

    h-index

  3. YO
    Yew-Soon Ong

    Nanyang Technological University, Singapore

    1 publications · 45 citations

    1

    h-index

  4. AY
    Alireza Yousefpour

    University of Technology Malaysia, Malaysia

    1 publications · 71 citations

    1

    h-index

  5. DV
    Deepali Vora

    Symbiosis International University, India

    1 publications · 30 citations

    1

    h-index

1–5 of 42

Venues

  1. 1

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  2. International Conference on Information Fusion

    Conference · 1 publications · 28 citations

    1

    h-index

  3. Expert Systems with Applications

    1 publications · 71 citations

    1

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  4. IEEE Transactions on Affective Computing

    TAC · 1 publications · 111 citations

    1

    h-index

  5. Institutional Research Information System (University of Udine)

    Repository · 1 publications · 39 citations

    1

    h-index

1–5