YAML Metadata Warning:The task_categories "sentiment-analysis" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

💰 Financial Sentiment Analysis Dataset

A dataset containing financial news headlines and social media posts labeled with sentiment.

Designed for:

Financial NLP research
Market sentiment analysis
Trading signal modeling

📊 Dataset Statistics

Train: 30,000 samples
Validation: 5,000 samples
Test: 5,000 samples
Total: 40,000 samples

📄 Data Format

{ "text": "Tesla stock surges after strong earnings report.", "sentiment": "positive", "source": "news", "asset_type": "stock" }

Sentiment Labels:

positive
neutral
negative

🎯 Intended Use

Sentiment classification models
Financial forecasting pipelines
NLP benchmarking

⚠️ Limitations

English only
Short-form text focused

Downloads last month: 9

Total file size:

4.38 kB