nanelimon/complaint-classification-dataset

Complaint Classification Dataset

Welcome to the complaint-classification-dataset! This dataset is designed for the classification of text complaints into various categories. It is hosted on Hugging Face and is ideal for training machine learning models to categorize textual complaints.

Overview

This dataset contains text complaints and their associated categories, sourced from Trendyol and Şikayetvar, popular platforms for online shopping and consumer complaints in Turkey. It is a valuable resource for natural language processing (NLP) tasks, specifically for text classification and sentiment analysis.

Dataset Details

• Dataset Name: complaint-classification-dataset
• Creator: nanelimon
• Hugging Face URL: Complaint Classification Dataset

Data Sources

• Trendyol: A major e-commerce platform in Turkey.
• Şikayetvar: A popular complaint and review platform in Turkey.

Features

The dataset includes the following features:

• text: The complaint text that needs to be classified.
• label: The classification label assigned to the complaint text.

Data Format

The dataset is available in CSV format. Each row contains:

• text: The text of the complaint.
• label: The category label.

Example:

text	category
rezalet bir ürün	1
bayıldım mükemmel	0

Getting Started

To use this dataset in your project, follow these steps:

Using the Dataset with Hugging Face Datasets Library

1. Install the Datasets Library

   If you haven’t already, install the datasets library from Hugging Face:

   pip install datasets
   

2. Load the Dataset

   Use the following code to load the dataset:

   from datasets import load_dataset
   
   dataset = load_dataset("nanelimon/complaint-classification-dataset")
   

Usage Examples

Text Classification

Here's a simple example of how to use this dataset for text classification:

from transformers import pipeline

# Load the dataset
from datasets import load_dataset
dataset = load_dataset("nanelimon/complaint-classification-dataset")

# Initialize a text classification pipeline
classifier = pipeline("text-classification")

# Sample text for classification
text = "Ürün hasarlı olarak elime ulaştı."

# Perform classification
result = classifier(text)
print(result)

License

The dataset is provided under the license specified by the creator. Please refer to the dataset card on Hugging Face for more details.

Contributing

If you have suggestions or improvements, please feel free to open an issue or submit a pull request. Contributions are always welcome!

Contact

For any questions or further information, you can reach out to the dataset creator:

Şeyma SARIGİL Hilal TABAK

• Creator: nanelimon
• Hugging Face Profile: nanelimon