metadata

license: cc-by-nc-sa-4.0
tags:
  - croissant
  - idrama-lab
  - social-media
  - rumble-platform
  - youtube
pretty_name: idrama-rumble-2024
source_datasets:
  - original
dataset_info:
  - config_name: face_embeddings
    features:
      - name: x1
        dtype: float64
      - name: x2
        dtype: float64
      - name: y1
        dtype: float64
      - name: y2
        dtype: float64
      - name: height
        dtype: float64
      - name: width
        dtype: float64
      - name: embedding
        sequence: float32
      - name: v_id
        dtype: string
      - name: filename
        dtype: string
      - name: channel_name_lower
        dtype: string
    splits:
      - name: train
        num_bytes: 859377822
        num_examples: 399333
    download_size: 1077273116
    dataset_size: 859377822
  - config_name: representative_images
    features:
      - name: image
        dtype: image
      - name: channel_name_lower
        dtype: string
      - name: v_id
        dtype: string
      - name: filename
        dtype: string
    splits:
      - name: train
        num_bytes: 29786708764.246
        num_examples: 252387
    download_size: 23599930820
    dataset_size: 29786708764.246
  - config_name: speaker_diarization
    features:
      - name: data
        dtype: string
      - name: v_id
        dtype: string
    splits:
      - name: train
        num_bytes: 175609236
        num_examples: 6715
    download_size: 27025049
    dataset_size: 175609236
  - config_name: transcripts
    features:
      - name: v_id
        dtype: string
      - name: transcription
        dtype: string
      - name: named_entities
        dtype: string
    splits:
      - name: train
        num_bytes: 6863296262
        num_examples: 6735
    download_size: 1963541596
    dataset_size: 6863296262
configs:
  - config_name: face_embeddings
    data_files:
      - split: train
        path: face_embeddings/train-*
  - config_name: representative_images
    data_files:
      - split: train
        path: representative_images/train-*
  - config_name: speaker_diarization
    data_files:
      - split: train
        path: speaker_diarization/train-*
  - config_name: transcripts
    data_files:
      - split: train
        path: transcripts/train-*
size_categories:
  - 100K<n<1M
language:
  - en

Dataset Summary

iDRAMA-rumble-2024 is a large-scale dataset of 6,735 podcast videos from Rumble, an alternative Youtube-like platform. Using state-of-the-art models, we extract information across three modalities: 1) text, 2) audio, and 3) video. We detail the methodology for extracting information from podcast videos in the paper and release a first-of-its-kind dataset including data from different modalities:

Metadata: Details about podcast videos, e.g., channel name, video name, video description, and more.
Text: Transcription (i.e., speech-to-text) of podcast videos.
Audio: Speaker diarization information providing speaker detection over time for each video.

Video: Sampled representative video frames from each video, totaling 200K images. We also detect more than 400K non-unique faces from these images and release face embeddings.

Repo-links	Purpose
Zenodo	On Zenodo, we provide JSON formatted dataset for all modalities and representative images in a zip file.
Github	The main repository of this dataset, where we provide code-snippets to get started with this dataset.
Huggingface	On Huggingface, we provide a dataset that can be accessed through Huggingface APIs in a `parquet` format.

Rumble platform: Rumble
Link to paper: CySoc 2024
License: CC BY-NC-SA 4.0

Quick start with Datasets

Install Datasets module by pip install datasets and then use the following code:

from datasets import load_dataset

# Download & Load complete dataset
dataset = load_dataset("iDRAMALab/iDRAMA-rumble-2024")

# Load dataset with specific config
dataset = load_dataset("iDRAMALab/iDRAMA-rumble-2024", name="transcripts")

More code-snippets to load the different variant of datasets efficiently are available on Github rpository.

Dataset Info

Dataset is organized by modalities -- transcripts, representative-images, speaker-diarization, and face-embeddings.

Config	Data-points
Podcast videos	6,735
Representative images	252,387
Face embeddings	399,333
Transcripts & Speaker diarization	6,735

Version

Maintenance Status: Active
Version Details:
- Current Version: v1.0.0
- First Release: 06/03/2024
- Last Update: 06/03/2024

Authorship

This dataset is published at "Workshop Proceedings of the 18th International AAAI Conference on Web and Social Media" hosted at Buffalo, NY, USA.

Academic Organization: iDRAMA Lab
Authors: Utkucan Balci, Jay Patel, Berkan Balci, Jeremy Blackburn
Affiliation: Binghamton University

Licensing

This dataset is available for free to use under terms of the non-commercial license CC BY-NC-SA 4.0.

Citation

@article{balci2024idrama,
  title  = {iDRAMA-rumble-2024: A Dataset of Podcasts from Rumble Spanning 2020 to 2022},
  author = {Balci, Utkucan and Patel, Jay and Balci, Berkan and Blackburn, Jeremy},
  year   = {2024},
  journal = {Workshop Proceedings of the 18th International AAAI Conference on Web and Social Media}
}