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Sentiment Analysis datasets
archive 2025-07-28104 datasets carry the task tag "Sentiment Analysis" (the task itself: Sentiment Analysis), ordered by the archive's paper count. Page 1 of 3: 48 shown of 104. 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 50 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
All 12,172
Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52
Sentiment Analysis datasets 1–48 of 104
SST (Stanford Sentiment Treebank)
The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language.
2,354 papers · 6 benchmarks
The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language.
1,808 papers · 2 benchmarks
The IMDb Movie Reviews dataset is a binary sentiment analysis dataset consisting of 50,000 reviews from the Internet Movie Database (IMDb) labeled as positive or negative.
1,787 papers · 9 benchmarks
The SST-5, also known as the Stanford Sentiment Treebank with 5 labels, is a dataset used for sentiment analysis.
338 papers · 2 benchmarks
MPQA Opinion Corpus (Multi-Perspective Question Answering)
The MPQA Opinion Corpus contains 535 news articles from a wide variety of news sources manually annotated for opinions and other private states (i.e., beliefs, emotions, sentiments, speculations, etc.).
313 papers · 3 benchmarks
ReDial (Recommendation Dialogues) is an annotated dataset of dialogues, where users recommend movies to each other.
105 papers · 2 benchmarks
The Yelp Dataset is a valuable resource for academic research, teaching, and learning.
86 papers · 15 benchmarks
TweetEval introduces an evaluation framework consisting of seven heterogeneous Twitter-specific classification tasks.
84 papers · 1 benchmark
The Multi-Domain Sentiment Dataset contains product reviews taken from Amazon.com from many product types (domains).
54 papers · 1 benchmark
ASTD (Arabic Sentiment Tweets Dataset)
Arabic Sentiment Tweets Dataset (ASTD) is an Arabic social sentiment analysis dataset gathered from Twitter.
31 papers · 1 benchmark
The SemEval-2013 Task 2 dataset contains data for two subtasks: A, an expression-level subtask, and B, a message-level subtask.
31 papers · 0 benchmarks
MR (MR Movie Reviews)
MR Movie Reviews is a dataset for use in sentiment-analysis experiments.
28 papers · 3 benchmarks
27 papers · 0 benchmarks
CH-SIMS is a Chinese single- and multimodal sentiment analysis dataset which contains 2,281 refined video segments in the wild with both multimodal and independent unimodal annotations.
25 papers · 1 benchmark
SLUE (Spoken Language Understanding Evaluation)
Spoken Language Understanding Evaluation (SLUE) is a suite of benchmark tasks for spoken language understanding evaluation.
22 papers · 3 benchmarks
DAiSEE is a multi-label video classification dataset comprising of 9,068 video snippets captured from 112 users for recognizing the user affective states of boredom, confusion, engagement, and frustration "in the wild".
17 papers · 1 benchmark
LABR (Large-Scale Arabic Book Reviews)
LABR is a large sentiment analysis dataset to-date for the Arabic language.
17 papers · 1 benchmark
NoReC (Norwegian Review Corpus)
The Norwegian Review Corpus (NoReC) was created for the purpose of training and evaluating models for document-level sentiment analysis.
17 papers · 0 benchmarks
iSarcasm is a dataset of tweets, each labelled as either sarcastic or nonsarcastic.
17 papers · 1 benchmark
DynaSent is an English-language benchmark task for ternary (positive/negative/neutral) sentiment analysis.
16 papers · 1 benchmark
IndicGLUE (Indic General Language Understanding Evaluation Benchmark)
We now introduce IndicGLUE, the Indic General Language Understanding Evaluation Benchmark, which is a collection of various NLP tasks as de- scribed below.
16 papers · 4 benchmarks
ArSarcasm-v2 is an extension of the original ArSarcasm dataset published along with the paper From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset.
15 papers · 0 benchmarks
ArSarcasm is a new Arabic sarcasm detection dataset.
14 papers · 0 benchmarks
PANDORA is the first large-scale dataset of Reddit comments labeled with three personality models (including the well-established Big 5 model) and demographics (age, gender, and location) for more than 10k users.
14 papers · 0 benchmarks
SentNoB (SentNoB: A Dataset for Analysing Sentiment on Noisy Bangla Texts)
Social Media User Sentiment Analysis Dataset.
12 papers · 0 benchmarks
ASC (TIL, 19 tasks) (Task Incremental Aspect Sentiment Classification)
A set of 19 ASC datasets (reviews of 19 products) producing a sequence of 19 tasks.
11 papers · 1 benchmark
Perspectrum is a dataset of claims, perspectives and evidence, making use of online debate websites to create the initial data collection, and augmenting it using search engines in order to expand and diversify the dataset.
11 papers · 1 benchmark
TaPaCo is a freely available paraphrase corpus for 73 languages extracted from the Tatoeba database.
11 papers · 0 benchmarks
SST-3 (Stanford Sentiment Treebank: 3-way)
SST-5 is the Stanford Sentiment Treebank 5-way classification dataset (positive, somewhat positive, neutral, somewhat negative, negative).
10 papers · 1 benchmark
HappyDB is a corpus of 100,000 crowdsourced happy moments.
9 papers · 0 benchmarks
MFRC (Moral Foundations Reddit Corpus)
Moral Foundations Reddit Corpus (MFRC) is a collection of 16,123 Reddit comments that have been curated from 12 distinct subreddits, hand-annotated by at least three trained annotators for 8 categories of moral sentiment (i.e., Care,…
9 papers · 0 benchmarks
TSAC (Tunisian Sentiment Analysis Corpus)
Tunisian Sentiment Analysis Corpus (TSAC) is a Tunisian Dialect corpus of 17.000 comments from Facebook.
9 papers · 0 benchmarks
The Arabic Sentiment Twitter Dataset for the Levantine dialect (ArSenTD-LEV) is a dataset of 4,000 tweets with the following annotations: the overall sentiment of the tweet, the target to which the sentiment was expressed, how the…
8 papers · 0 benchmarks
L3CubeMahaSent is a large publicly available Marathi Sentiment Analysis dataset.
8 papers · 0 benchmarks
MultiBooked is a dataset for supervised aspect-level sentiment analysis in Basque and Catalan, both of which are under-resourced languages.
8 papers · 0 benchmarks
PHINC is a parallel corpus of the 13,738 code-mixed English-Hindi sentences and their corresponding translation in English.
8 papers · 0 benchmarks
SubjQA is a question answering dataset that focuses on subjective (as opposed to factual) questions and answers.
8 papers · 0 benchmarks
JGLUE, Japanese General Language Understanding Evaluation, is built to measure the general NLU ability in Japanese.
7 papers · 0 benchmarks
A sentiment analysis Tunisian Arabizi Dataset, collected from social networks, preprocessed for analytical studies and annotated manually by Tunisian native speakers.
7 papers · 0 benchmarks
DSC (10 tasks) (Task Incremental Document Sentiment Classification)
A set of 10 DSC datasets (reviews of 10 products) to produce sequences of tasks.
6 papers · 1 benchmark
A multimodal dataset for sentiment analysis on internet memes.
6 papers · 0 benchmarks
PerSenT is a dataset of crowd-sourced annotations of the sentiment expressed by the authors towards the main entities in news articles.
5 papers · 0 benchmarks
RuSentRel is a corpus of analytical articles translated into Russian texts in the domain of international politics obtained from foreign authoritative sources.
5 papers · 0 benchmarks
Amazon Fine Foods is a dataset that consists of reviews of fine foods from amazon.
4 papers · 0 benchmarks
Chinese AI and Law 2019 Similar Case Matching dataset.
4 papers · 0 benchmarks
GeoCoV19 is a large-scale Twitter dataset containing more than 524 million multilingual tweets.
4 papers · 0 benchmarks
Laptop-ACOS is a brand new Laptop dataset collected from the Amazon platform in the years 2017 and 2018 (covering ten types of laptops under six brands such as ASUS, Acer, Samsung, Lenovo, MBP, MSI, and so on).
4 papers · 1 benchmark
The Restaurant-ACOS dataset is constructed based on the SemEval 2016 Restaurant dataset (Pontiki et al., 2016) and its expansion datasets (Fan et al., 2019; Xu et al., 2020).
4 papers · 1 benchmark
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.