Tweet Sentiment Analysis

Tweet Sentiment Analysis is a computational task within opinion mining that involves identifying and extracting subjective information in the form of sentiment polarity—positive, negative, or neutral—from individual Twitter posts as its primary textual unit.

3.8K

Publications

266.5K

Citations

10.4K

Authors

2.7K

Institutions

Publications per year

2017–2026

2.6K

Authors

10.4K

  1. SM
    Saif M. Mohammad

    National Research Council Canada, Canada

    20 publications · 3.6K citations

    18

    h-index

  2. EC
    Erik Cambria

    Nanyang Technological University, Singapore

    17 publications · 3.6K citations

    16

    h-index

  3. JR
    José Ramón Saura

    Universidad Rey Juan Carlos, Spain

    16 publications · 1.3K citations

    16

    h-index

  4. SK
    Svetlana Kiritchenko

    National Research Council Canada, Canada

    16 publications · 4.3K citations

    15

    h-index

  5. IA
    Imran Ashraf

    Yeungnam University, South Korea

    15 publications · 1.1K citations

    14

    h-index

1–5 of 10.4K

Venues

  1. IEEE Access

    72 publications · 5.8K citations

    39

    h-index

  2. Expert Systems with Applications

    45 publications · 7.2K citations

    35

    h-index

  3. Procedia Computer Science

    49 publications · 3.7K citations

    33

    h-index

  4. Journal of Medical Internet Research

    46 publications · 4.1K citations

    33

    h-index

  5. arXiv (Cornell University)

    Repository · 93 publications · 4.8K citations

    32

    h-index

1–5