Mention counts below measure name matches in tracked papers, not benchmark quality or downloads. A family count can cover multiple datasets; it is not a separate count for each comparison row. Choose a task and version first, preserve evaluation splits, and follow the linked release terms. The site's content license does not replace the datasets' own terms.
NLP dataset comparison: tasks, access and usage conditions
Dataset / version
Task and evaluation
Access and preparation
Usage conditions
Stanford Sentiment Treebank (SST)
Sentence and phrase sentiment; SST-2 is binary, SST-5 uses five labels.
Evaluation: Accuracy; sentence-only and phrase-augmented experiments are not directly equivalent.
From Nov 2023 to Oct 2026, 53 archived papers mentioned Stanford Sentiment Treebank in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Dec 2024 (6).
No paper of the tracked journals mentioned Stanford Sentiment Treebank in the last 30 days (2026-10-07 to 2026-11-05).
From 2017 to 2026 (so far), Stanford Sentiment Treebank was mentioned in 58 papers in the tracked journals, most of them in AI (54), information systems (1) and finance (1).
10 of them were published in 2025, against 0 in 2017.
Since 2023, the institutions with the most of these papers were Nanyang Technological University (5), Chinese Academy of Sciences (4) and The University of Sydney (4).
The journals publishing most of them were IEEE Transactions on Neural Networks and Learning Systems (7), Artificial Intelligence Review (5) and Neural Networks (5).
The most-cited of them is “Vision-Language Models for Vision Tasks: A Survey” (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024), with 998 citations.
Papers use Stanford Sentiment Treebank most often with Natural language inference (SNLI, MultiNLI) (27), IMDb (21) and GLUE / SuperGLUE (19); it has 33 partners in the code and data network, in the group around Twitter / X, Facebook, YouTube / TikTok.
Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.
Papers use Stanford Sentiment Treebank most often with Natural language inference (SNLI, MultiNLI) (27), IMDb (21) and GLUE / SuperGLUE (19); it has 33 partners in the code and data network, in the group around Twitter / X, Facebook, YouTube / TikTok. The whole network →
What papers use Stanford Sentiment Treebank together with (at least 3 papers; lift 1 = chance)
Scholar4AI. (2026). Stanford Sentiment Treebank. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/stanford-sentiment-treebank
@misc{scholar4ai-datasets-stanford-sentiment-treebank,
author = {{Scholar4AI}},
title = {Stanford Sentiment Treebank},
year = {2026},
howpublished = {\url{https://scholar4ai.com/datasets/stanford-sentiment-treebank}},
urldate = {2026-11-05},
note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).