kazanova/sentiment140: papers linking to it

Kaggle · www.kaggle.com/datasets/kazanova/sentiment140

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to kazanova/sentiment140 (https://www.kaggle.com/datasets/kazanova/sentiment140), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

6 papers in the tracked journals link to the Kaggle dataset kazanova/sentiment140 in their Crossref records, the first in 2022; most of them (3) in 2023.
By category: AI (6); the journals with the most are Journal Of Big Data (2), Expert Systems with Applications (1) and Knowledge-Based Systems (1).

By year#

20222026

Papers linking to kazanova/sentiment140 by publication year
Year	Papers
2022	1
2023	3
2024	1
2026	1

Journals#

Journals whose papers link to kazanova/sentiment140 most
Journal	Papers
Journal Of Big Data	2
Expert Systems with Applications	1
Knowledge-Based Systems	1
Language Resources and Evaluation	1
Knowledge and Information Systems	1

Papers linking to kazanova/sentiment140, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-04-17	Twitter sentiment analysis using hybrid gated attention recurrent network	Journal Of Big Data	Nikhat Parveen, Prąsun Chakrabarti, Bùi Thanh Hùng et al.	87	cites it
2023-03-11	An efficient model for sentiment analysis using artificial rabbits optimized vector functional link network	Expert Systems with Applications	Dharmendra Dangi, Sonal Telang Chandel, Dheeraj Kumar Dixit et al.	37	cites it
2023-03-22	Social network analysis for crime rate detection using Spizella swarm optimization based BiLSTM classifier	Knowledge-Based Systems	Pooja Mithoo, Manoj Kumar	15	cites it
2022-02-25	Commonsense based text mining on urban policy	Language Resources and Evaluation	Manish Puri, Aparna S. Varde, Gerard de Melo	14	cites it
2024-12-18	A hybrid Hadoop-based sentiment analysis classifier for tweets associated with COVID-19 utilizing two machine learning algorithms: CNN, and fuzzy C4.5	Journal Of Big Data	Fatima Es-sabery, Ibrahim Es-sabery, Junaid Qadir et al.	8	cites it
2026-02-25	Optimizing sentiment analysis: a hybrid approach with heuristic optimization	Knowledge and Information Systems	Indira Priyadarshini Tummala, R. B. V. Subramanyam	1	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). kazanova/sentiment140: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-kazanova-sentiment140

@misc{scholar4ai-code-kaggle-kazanova-sentiment140,
  author = {{Scholar4AI}},
  title = {kazanova/sentiment140: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-kazanova-sentiment140}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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