Search Autocomplete Analysis

Search Autocomplete Analysis is a computational method within search analytics that systematically examines and interprets the real-time suggestions generated by search engines during query formulation to infer user intent, behavioral patterns, and information needs.

10

Publications

424

Citations

39

Authors

24

Institutions

Publications per year

2017–2026

8

Authors

39

  1. DV
    Dániel V. Veres

    Semmelweis University, Hungary

    1 publications · 19 citations

    1

    h-index

  2. KY
    Kan Yuan

    Indiana University Bloomington, United States

    1 publications · 20 citations

    1

    h-index

  3. YH
    Yidnekachew Haile

    King's College London, United Kingdom

    1 publications · 63 citations

    1

    h-index

  4. PB
    Paul Baker

    Lancaster University, United Kingdom

    1 publications · 132 citations

    1

    h-index

  5. SJ
    Shan Jiang

    University of Arizona, United States

    1 publications · 52 citations

    1

    h-index

1–5 of 39

Venues

  1. Telematics and Informatics

    1 publications · 15 citations

    1

    h-index

  2. Nucleic Acids Research

    1 publications · 19 citations

    1

    h-index

  3. Critical Discourse Studies

    1 publications · 132 citations

    1

    h-index

  4. Information Processing & Management

    1 publications · 17 citations

    1

    h-index

  5. GEMA Online Journal of Language Studies

    1 publications · 14 citations

    1

    h-index

1–5