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Twitter Sentiment Analysis datasets

archive 2025-07-28

7 datasets carry the task tag "Twitter Sentiment Analysis" (the task itself: Twitter Sentiment Analysis), ordered by the archive's paper count. Page 1 of 1: 7 shown of 7. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Twitter Sentiment Analysis datasets 1–7 of 7

Twitter Sentiment Analysis (Entity-Level Twitter Sentiment Analysis Dataset)
This is an entity-level Twitter Sentiment Analysis dataset.
4 papers · 1 benchmark
RETWEET is a dataset of tweets and overall predominant sentiment of their replies.
3 papers · 2 benchmarks
Sentiment detection remains a pivotal task in natural language processing, yet its development in Arabic lags due to a scarcity of training materials compared to English.
2 papers · 0 benchmarks
chinahate dataset contains a total of 2,172,333 tweets hashtagged #china posted during the time it was collected.
1 paper · 0 benchmarks
The dataset contains 30 million cryptocurrency-related tweets from 10.10.2020 to 3.3.2021.
1 paper · 0 benchmarks
This dataset was created as part of the Master's thesis titled "Multi-Class Depression Detection Through Tweets Using Artificial Intelligence." It contains tweets labeled for five types of depression (Bipolar, Major, Psychotic, Atypical,…
1 paper · 0 benchmarks
SentimentArcs’ reference corpus for novels consists of 25 narratives selected to create a diverse set of well recognized novels that can serve as a benchmark for future studies.
1 paper · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.