datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
twitter-financial-news-sentiment
Dataset Description
The Twitter Financial News dataset is an English-language dataset containing an annotated corpus of finance-related tweets. This dataset is used to classify finance-related tweets for their sentiment.
The dataset holds 11,932 documents annotated with 3 labels:
sentiments = {
"LABEL_0": "Bearish",
"LABEL_1": "Bullish",
"LABEL_2": "Neutral"
}
The data was collected using the Twitter API. The current dataset supports the multi-class classification… See the full description on the dataset page: https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment.twitter-airline-sentiment
Dataset Card for Twitter US Airline Sentiment
Dataset Summary
This data originally came from Crowdflower's Data for Everyone library.
As the original source says,
A sentiment analysis job about the problems of each major U.S. airline. Twitter data was scraped from February of 2015 and contributors were asked to first classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service").
The data we're… See the full description on the dataset page: https://huggingface.co/datasets/osanseviero/twitter-airline-sentiment.Persian_sentimentturkish-sentiment-analysis-dataset
Dataset
This dataset contains positive , negative and notr sentences from several data sources given in the references. In the most sentiment models , there are only two labels; positive and negative. However , user input can be totally notr sentence. For such cases there were no data I could find. Therefore I created this dataset with 3 class. Positive and negative sentences are listed below. Notr examples are extraced from turkish wiki dump. In addition, added some random text… See the full description on the dataset page: https://huggingface.co/datasets/winvoker/turkish-sentiment-analysis-dataset.amazon-reviews-sentiment-analysis
Dataset Card for amazon reviews for sentiment analysis
Dataset Summary
One of the most important problems in e-commerce is the correct calculation of the points given to after-sales products. The solution to this problem is to provide greater customer satisfaction for the e-commerce site, product prominence for sellers, and a seamless shopping experience for buyers. Another problem is the correct ordering of the comments given to the products. The prominence of misleading… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/amazon-reviews-sentiment-analysis.snappfood-sentiment-analysisdigikala-sentiment-analysisMBTI-Sentimentmulticlass-sentiment-analysis-dataset
Dataset Card for Dataset Name
Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/Sp1786/multiclass-sentiment-analysis-dataset.Persian-Food-Sentiment
Persian Food Sentiment Dataset
This data is orinally from https://hooshvare.github.io/docs/datasets/sa.
BibTeX Citation
If you use this dataset, please cite following paper:
@article{ParsBERT,
title={ParsBERT: Transformer-based Model for Persian Language Understanding},
author={Mehrdad Farahani, Mohammad Gharachorloo, Marzieh Farahani, Mohammad Manthouri},
journal={ArXiv},
year={2020},
volume={abs/2005.12515}
}
multimodal-LLMs-See-Sentiment
MLLMsent — datasets and experiment results
Every input and every output of "Multimodal LLMs See Sentiment"
(arXiv:2508.16873): the image descriptions generated by six multimodal
LLMs, the sentiment labels derived from the PerceptSent annotations, and the complete
per-fold results of all 141 experiments.
Paper: arXiv:2508.16873
Code, training and inference: https://github.com/neemiasbsilva/multimodal-LLMs-see-sentiment
Model checkpoints:… See the full description on the dataset page: https://huggingface.co/datasets/neemiasbsilva/multimodal-LLMs-See-Sentiment.ru_sentiment_dataset
Dataset with sentiment of Russian text
Contains aggregated dataset of Russian texts from 6 datasets.
Labels meaning
0: NEUTRAL
1: POSITIVE
2: NEGATIVE
Datasets
Sentiment Analysis in Russian
Sentiments (positive, negative or neutral) of news in russian language from Kaggle competition.
Russian Language Toxic Comments
Small dataset with labeled comments from 2ch.hk and pikabu.ru.
Dataset of car reviews for machine learning (sentiment analysis)
Glazkova A.… See the full description on the dataset page: https://huggingface.co/datasets/MonoHime/ru_sentiment_dataset.Arabic_sentimentyoutube-comment-sentiment
YouTube Comments Sentiment Analysis Dataset (1M+ Labeled Comments)
Overview
This dataset comprises over one million YouTube comments, each annotated with sentiment labels—Positive, Neutral, or Negative. The comments span a diverse range of topics including programming, news, sports, politics and more, and are enriched with comprehensive metadata to facilitate various NLP and sentiment analysis tasks.
How to use:
import pandas as pd
df =… See the full description on the dataset page: https://huggingface.co/datasets/AmaanP314/youtube-comment-sentiment.sentiment_analysis_preprocessed_datasetBrief idea about dataset:
This dataset is designed for a Text Classification to be specific Multi Class Classification, inorder to train a model (Supervised Learning) for Sentiment Analysis.
Also to be able retrain the model on the given feedback over a wrong predicted sentiment this dataset will help to manage those things using Other Features.
Main Features
text
labels
This feature variable has all sort of texts, sentences, tweets, etc.
This target variable contains 3 types of… See the full description on the dataset page: https://huggingface.co/datasets/prasadsawant7/sentiment_analysis_preprocessed_dataset.hotel_reviews_sentiment_1KDataset source attributed to https://data.world/
Dataset contains user reviews for hotel stays, the original dataset from data.world was slightly modified to create sentiment and total_review columns based on the
ratings and review text from the original dataset
Sentiment140TwitterArabic_Sentiment_Datasetmultilingual-financial-sentiment
Multilingual Financial Sentiment Dataset
A curated dataset of 39,829 financial news sentences annotated with sentiment labels (Negative / Neutral / Positive) across 7 languages, collected from 80+ financial news sources worldwide.
Dataset Summary
Total samples
39,829
Languages
7 (EN, ZH, JA, DE, FR, ES, AR)
Labels
3 (negative, neutral, positive)
Format
CSV
Sources
80+ financial news outlets
Languages
Language
Code
Samples
%… See the full description on the dataset page: https://huggingface.co/datasets/Kenpache/multilingual-financial-sentiment.product-reviews-sentiment
Product Reviews Sentiment
9,000 English customer reviews labeled into 4 operational categories, balanced across classes, ready for training text classifiers.
Built for the common real-world triage task: routing incoming customer feedback to the right team. The four categories map to the four owners most support pipelines route to: product, support, fraud, and operations.
Categories
Category
Rows
What it covers
Product Feedback
2,238
Quality, features… See the full description on the dataset page: https://huggingface.co/datasets/AnkitAI/product-reviews-sentiment.Amazon_Reviews_Binary_for_Sentiment_Analysis
Dataset Card for Dataset Name
The Amazon reviews polarity dataset is constructed by taking review score 1 and 2 as negative, and 4 and 5 as positive. Samples of score 3 is ignored. In the dataset, class 1 is the negative and class 2 is the positive. Each class has 1,800,000 training samples and 200,000 testing samples.
Dataset Details
Dataset Description
The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 3… See the full description on the dataset page: https://huggingface.co/datasets/yassiracharki/Amazon_Reviews_Binary_for_Sentiment_Analysis.Turkish_SentimentAnalysis_TRSAv1TRSAv1 (Turkish Sentiment Analysis Version 1) Dataset
This data set has been produced to contribute to Turkish NLP studies.
The dataset consists of a total of 150 thousand samples, 50 thousand negative, 50 thousand positive, and 50 thousand neutral.
It can be used in text classification and sentiment analysis studies by citing the related study.
Related Work
Aydoğan M, Kocaman V. TRSAv1: A new benchmark dataset for classifying user reviews on Turkish e-commerce websites. Journal of… See the full description on the dataset page: https://huggingface.co/datasets/maydogan/Turkish_SentimentAnalysis_TRSAv1.Amazon_Reviews_for_Sentiment_Analysis_fine_grained_5_classes
Dataset Card for Dataset Name
The Amazon reviews full score dataset is constructed by randomly taking 600,000 training samples and 130,000 testing samples for each review score from 1 to 5. In total there are 3,000,000 trainig samples and 650,000 testing samples.
Dataset Details
Dataset Description
The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 3 columns in them, corresponding to class index (1 to 5)… See the full description on the dataset page: https://huggingface.co/datasets/yassiracharki/Amazon_Reviews_for_Sentiment_Analysis_fine_grained_5_classes.finance-news-sentiment-35k
Finance News Sentiment 40k
39,965 English financial news headlines, collected from public Telegram
finance news-wire channels, labeled for 3-class sentiment (positive / negative / neutral) and a secondary
topic label, by two independent LLM judges from different model families with
an arbiter settling disputes.
A FinBERT model fine-tuned on this data reaches test accuracy 0.847 / macro F1
0.810: remehostingservices/finbert-finance-news-sentiment.
Code, training scripts and the… See the full description on the dataset page: https://huggingface.co/datasets/remehostingservices/finance-news-sentiment-35k.sentiment中文外卖 10k 评论数据集。
aomen-2024-sentiment-details2024年所有的评论和评分，来自携程平台，澳门所有景点
kaggle-financial-sentimentarabic-sentiments2LLMs-Sentiment-Augmented-Bitcoin-Dataset
Leveraging LLMs for Informed Bitcoin Trading Decisions: Prompting with Social and News Data Reveals Promising Predictive Abilities
The work was carried out by:
Danilo Corsi
Cesare Campagnano
Description
This project investigates the potential of leveraging Large Language Models (LLMs) to support Bitcoin traders. Specifically, we analyze the correlation between Bitcoin price movements and sentiment expressed in news headlines, posts, and comments on social media.
We… See the full description on the dataset page: https://huggingface.co/datasets/danilocorsi/LLMs-Sentiment-Augmented-Bitcoin-Dataset.twitter_sentiment_analysis