Datasetpublic

pkchwy/turkish-comprehensive-movie-series-dataset

Beyazperde Film & Series Dataset This dataset contains a comprehensive collection of Turkish films and TV series from Beyazperde.com, including detailed information about movies, series, cast, reviews, and ratings. Dataset Summary Total Movies: 27,227 Total Series: 11,240 Total Entries: 38,467 File Size: ~222 MB Format: JSONL (JSON Lines) Language: Turkish Source: Beyazperde.com Data Structure Each line in the JSONL file contains a JSON object… See the full description on the dataset page: https://huggingface.co/datasets/pkchwy/turkish-comprehensive-movie-series-dataset.

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Dataset Card

Beyazperde Film & Series Dataset

This dataset contains a comprehensive collection of Turkish films and TV series from Beyazperde.com, including detailed information about movies, series, cast, reviews, and ratings.

Dataset Summary

—Total Movies: 27,227
—Total Series: 11,240
—Total Entries: 38,467
—File Size: ~222 MB
—Format: JSONL (JSON Lines)
—Language: Turkish
—Source: Beyazperde.com

Data Structure

Each line in the JSONL file contains a JSON object with either a movie or series:

Movie Example

json

{
  "id": "268495",
  "title": "Deccal 3",
  "url": "https://www.beyazperde.com/filmler/film-268495/",
  "type": "movie",
  "poster_url": "https://tr.web.img3.acsta.net/c_310_420/commons/v9/common/empty/empty_portrait.png",
  "genres": ["Korku", "Gerilim"],
  "detailed_synopsis": "Korku ve gerilim türündeki Deccal serisinin devam halkası...",
  "director": "Director Name",
  "cast": ["Actor 1", "Actor 2"],
  "duration": "120 min",
  "release_date": "2024",
  "rating": "7.5/10",
  "screenwriter": "Writer Name",
  "beyazperde_review_title": "Review Title",
  "beyazperde_review_text": "Review content...",
  "beyazperde_review_score": "8/10",
  "beyazperde_review_author": "Reviewer Name"
}

Series Example

json

{
  "id": "5063",
  "title": "The Teenage mutant ninja turtles 2003",
  "url": "https://www.beyazperde.com/diziler/dizi-5063/",
  "type": "series",
  "poster_url": "https://tr.web.img4.acsta.net/c_310_420/medias/nmedia/18/69/07/58/18863307.jpg",
  "genres": ["Aksiyon", "Animasyon", "Komedi"],
  "episode_duration": "24 Dak.",
  "detailed_synopsis": "Series description...",
  "creator": "Creator Name",
  "total_seasons": "4"
}

Data Fields

Common Fields (100% coverage)

Field	Type	Description
`id`	string	Unique ID
`title`	string	Title
`url`	string	Beyazperde page URL
`type`	string	"movie" or "series"
`poster_url`	string	Poster image URL
`genres`	array	Genres

Movie-Specific Fields

Field	Type	Coverage	Description
`detailed_synopsis`	string	91.4%	Plot summary
`director`	string	93.3%	Director name
`cast`	array	96.0%	Actor names
`duration`	string	87.5%	Movie duration
`release_date`	string	33.7%	Release date
`rating`	string	16.7%	User rating
`screenwriter`	string	89.1%	Screenwriter
`beyazperde_review_*`	string	15-17%	Official reviews

Series-Specific Fields

Field	Type	Coverage	Description
`episode_duration`	string	83.4%	Episode duration
`detailed_synopsis`	string	37.3%	Series description
`creator`	string	33.2%	Series creator
`total_seasons`	string	37.1%	Number of seasons

Usage

Loading with Hugging Face Datasets

python

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("json", data_files="dataset.jsonl")

# Access the data
print(f"Total entries: {len(dataset['train'])}")
print(f"First entry: {dataset['train'][0]}")

# Filter by type
movies = dataset['train'].filter(lambda x: x['type'] == 'movie')
series = dataset['train'].filter(lambda x: x['type'] == 'series')

print(f"Movies: {len(movies)}")
print(f"Series: {len(series)}")

Loading with Python

python

import json

# Loading JSONL file
data = []
with open('dataset.jsonl', 'r', encoding='utf-8') as f:
    for line in f:
        data.append(json.loads(line))

print(f"Loaded {len(data)} entries")
print(f"First entry: {data[0]['title']}")

Analysis with Pandas

python

import pandas as pd
import json

# Load JSONL file
data = []
with open('dataset.jsonl', 'r', encoding='utf-8') as f:
    for line in f:
        data.append(json.loads(line))

df = pd.DataFrame(data)

# Basic statistics
print(f"Total entries: {len(df)}")
print(f"Movies: {len(df[df['type'] == 'movie'])}")
print(f"Series: {len(df[df['type'] == 'series'])}")

# Genre analysis
all_genres = []
for genres in df['genres'].dropna():
    if isinstance(genres, list):
        all_genres.extend(genres)

genre_counts = pd.Series(all_genres).value_counts()
print(f"Most popular genres: {genre_counts.head()}")

Advanced Filtering

python

# Filter horror movies
horror_movies = dataset['train'].filter(
    lambda x: x['type'] == 'movie' and 
    'Korku' in x.get('genres', [])
)

# Filter recent movies (with release date)
recent_movies = dataset['train'].filter(
    lambda x: x['type'] == 'movie' and 
    x.get('release_date', '').isdigit() and 
    int(x['release_date']) >= 2020
)

# Filter movies with reviews
reviewed_movies = dataset['train'].filter(
    lambda x: x['type'] == 'movie' and 
    x.get('beyazperde_review_text', '') != ''
)

Use Cases

This dataset can be used for:

🎬 Turkish Content Recommendation Systems

—Collaborative filtering based on Turkish user preferences
—Content-based recommendation (genre, director, actor similarity)
—Cross-language recommendation systems

📝 Natural Language Processing (Turkish)

—Sentiment analysis on Turkish film reviews
—Text classification (genre prediction from Turkish synopsis)
—Turkish text generation and summarization

📊 Turkish Film Industry Analysis

—Turkish cinema trend analysis
—Director and actor popularity in Turkey
—Genre distribution in Turkish media
—TV series vs movie popularity analysis

🌍 Multilingual Applications

—Turkish-English content matching
—Cross-cultural recommendation systems
—International content localization

Data Quality

—Missing Data: Some entries may lack synopsis, cast, or review information
—Language: Primarily Turkish content with some English titles
—Time Range: Films and series from various years
—Scope: Popular Turkish and international content on Beyazperde platform
—Reviews: Official Beyazperde reviews available for ~17% of movies

Ethical Use and Limitations

—This dataset consists of publicly available Beyazperde.com data
—Contains no personal information
—Check Beyazperde terms of service before commercial use
—Possible sampling bias (popular content weighted)
—Respect Turkish content creators' rights

Citation

If you use this dataset in your research or projects, please cite it as:

bibtex

@dataset{beyazperde_film_series_dataset_2025,
  title={Turkish Film & Series Dataset},
  author={Salih Mert Canseven},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/pkchwy/turkish-comprehensive-movie-series-dataset}
}

Or in text format:

Salih Mert Canseven. (2025). Beyazperde Film & Series Dataset. Hugging Face. https://huggingface.co/datasets/pkchwy/turkish-comprehensive-movie-series-dataset

License

MIT License - Free for educational and research purposes. Citation required for any use.

Contact

For questions about the dataset, please use GitHub Issues.

Source: Beyazperde.com Last Updated: August 2025