Fine-grained Sentiment Classification

Fine-Grained Sentiment Classification is a sentiment analysis task that categorizes text into highly specific sentiment levels, such as very negative, negative, neutral, positive, and very positive, thereby distinguishing subtle affective variations beyond the broad positive/negative/neutral triad.

318

Publications

31.4K

Citations

985

Authors

395

Institutions

Publications per year

2017–2026

258

Authors

985

  1. JW
    Jin Wang

    Changsha University of Science and Technology, China

    5 publications · 997 citations

    5

    h-index

  2. KR
    K. Robert Lai

    Yuan Ze University, Taiwan

    4 publications · 967 citations

    4

    h-index

  3. SM
    Sebastiano Manzan

    Baruch College, United States

    4 publications · 209 citations

    4

    h-index

  4. LB
    Luca Barbaglia

    Baruch College, United States

    4 publications · 209 citations

    4

    h-index

  5. XZ
    Xuejie Zhang

    Yunnan University, China

    4 publications · 857 citations

    4

    h-index

1–5 of 985

Venues

  1. IEEE Access

    16 publications · 1.3K citations

    15

    h-index

  2. arXiv (Cornell University)

    Repository · 14 publications · 973 citations

    13

    h-index

  3. Knowledge-Based Systems

    12 publications · 971 citations

    12

    h-index

  4. Neurocomputing

    10 publications · 821 citations

    10

    h-index

  5. Expert Systems with Applications

    8 publications · 502 citations

    9

    h-index

1–5