---
annotations_creators:
- crowd-sourced
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: IMDB Multi-Movie Review Dataset
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---

# Dataset Card for IMDb Multi-Movie Review Dataset

## Dataset Summary

The IMDb Multi-Movie Review Dataset contains **approximately 114,000 user reviews** collected from **over 150 movies** on IMDb.  
Each movie is stored as a separate **JSON file**, identified by its `movie_id` (IMDb ID).  
Each JSON file includes a list of structured reviews, where every review consists of:

- `title`: A short summary or headline of the review.
- `review`: The full detailed user review.
- `rating`: A numeric rating (1–10) as a string.

This dataset supports tasks like **sentiment analysis**, **rating prediction**, and **text summarization** in the domain of movie reviews across multiple genres and time periods.

---

## Supported Tasks and Leaderboards

- **Sentiment Classification**: Predict sentiment from the review text. Can be used with custom or soft labels.
- **Rating Classification/Regression**: Predict a 1–10 score from the review text.
- **Summarization**: Generate a short title-style summary (`title`) from the full review (`review`).

---

## Languages

All reviews are written in **English**.

---

## Dataset Structure

Each JSON file follows this format:

```json
{
  "movie_id": "tt0085750",
  "reviews": [
    {
      "title": "Mediocre, but Oscar worthy compared to part IV.",
      "review": "Saw this one in all its 3D glory in the theater back in 1983...",
      "rating": "5"
    }
  ]
}
```

## 🔧 Load Dataset (from Hugging Face Hub)

```python
from datasets import load_dataset
dataset = load_dataset("Daksh0505/IMDB-Reviews")
print(dataset['train'][0])
```

## Citation (Please add if you use this dataset)

```ruby
@misc{imdb-multimovie-reviews,
  title = {IMDb Multi-Movie Review Dataset},
  author = {Daksh Bhardwaj},
  year = {2025},
  url = {https://huggingface.co/datasets/Daksh0505/IMDB-Reviews
  note = {Accessed: 2025-07-17}
}
```


📂 Dataset URL: [https://huggingface.co/datasets/Daksh0505/IMDB-Reviews](https://huggingface.co/datasets/Daksh0505/IMDB-Reviews)

## 🚀 Try the Live Demo

Click below to test both models live in your browser that are were trained on this dataset:

[![Open in Spaces](https://img.shields.io/badge/🤗%20Hugging%20Face-Sentiment%20Demo-blue?logo=streamlit&style=for-the-badge)](https://huggingface.co/spaces/Daksh0505/sentiment-model-comparison)