---
dataset_info:
  features:
  - name: Text
    dtype: string
  - name: Timestamp
    dtype: string
  - name: User
    dtype: string
  - name: Platform
    dtype: string
  - name: Hashtags
    dtype: string
  - name: Retweets
    dtype: float64
  - name: Likes
    dtype: float64
  - name: Country
    dtype: string
  - name: Year
    dtype: int64
  - name: Month
    dtype: int64
  - name: Day
    dtype: int64
  - name: Hour
    dtype: int64
  - name: Sentiment
    dtype: string
  splits:
  - name: train
    num_bytes: 198093
    num_examples: 732
  download_size: 78808
  dataset_size: 198093
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Sentiment Analysis Dataset  

## Description  
This dataset contains social media posts labeled with sentiment categories. It includes metadata such as user details, timestamps, engagement metrics, and hashtags, making it useful for sentiment analysis, natural language processing (NLP), and social media analytics.  

## Dataset Details  

### **Columns:**  
- **Text**: The content of the social media post.  
- **Sentiment**: The sentiment classification (**Positive, Negative, Neutral**).  
- **Timestamp**: The date and time when the post was made.  
- **User**: The username of the person who posted the content.  
- **Platform**: The social media platform (**Twitter, Instagram, Facebook, etc.**).  
- **Hashtags**: Hashtags used in the post.  
- **Retweets**: Number of retweets (for Twitter) or shares.  
- **Likes**: Number of likes the post received.  
- **Country**: The country from which the post originated.  
- **Year, Month, Day, Hour**: Extracted datetime components for time-based analysis.  

### **Notes:**  
- The dataset contains **732 entries**.  
- The **Unnamed: 0** and **Unnamed: 0.1** columns appear to be redundant and can be ignored.  
- This dataset can be used for **training sentiment classification models** or **analyzing engagement trends**.  

## Use Cases  
- **Sentiment analysis** of social media content.  
- **Engagement analysis** of posts based on likes and retweets.  
- **Trend analysis** of public opinion over time.  

## How to Use  
You can load the dataset using the `datasets` library:  
```python
from datasets import load_dataset

dataset = load_dataset("Tarakeshwaran/Hackathon_Sentiment_analysis")
print(dataset)