Datasets:

Tarakeshwaran
/

Hackathon_Sentiment_analysis

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:

from datasets import load_dataset

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