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Social Media Emotion Classification Dataset
Mental Health & Wellness
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Free
About
This dataset is designed for emotion identification within natural language processing (NLP) and data science projects. It serves as test data specifically for classifying emotions in tweets, enabling users to train and build robust models for emotional analysis. The content has been manually annotated using Best-Worst Scaling (BWS) to obtain reliable real-valued scores.
Columns
text: This column contains the tweet content.label: This column specifies the emotional category to which the tweet belongs. Unique values for this column include 'fear' (32% of data), 'anger' (24% of data), and 'Other' (44% of data), representing 3099 distinct categories in total.
Distribution
Data files are typically provided in CSV format. Specific numbers for rows or records are not available within the provided sources.
Usage
This dataset is ideal for:
- Training and building robust models for emotion analysis.
- Performing emotional analysis within various NLP and data science projects.
- Developing and evaluating text classification models focused on emotional sentiment.
Coverage
- Geographic Scope: The data is considered global in its scope.
- Time Range: The dataset was listed on 8th June 2025; however, the specific time range for the data collection itself is not provided.
- Demographic Scope: Not explicitly detailed, but implied by the nature of tweets to represent a broad range of public expressions.
License
CCO
Who Can Use It
This dataset is well-suited for:
- Data scientists and NLP practitioners seeking to build and enhance emotion classification models.
- Researchers focusing on computational approaches to subjectivity, sentiment, and social media analysis.
- Machine learning engineers developing applications that require understanding emotional nuances in text.
Dataset Name Suggestions
- Emotion Classification NLP Test Data
- Tweet Emotion Analysis Dataset
- Social Media Emotion Classification
- NLP Tweet Emotion Data
- Emotion Detection Tweets
Attributes
Original Data Source: Emotion Classification NLP
QUALITY