metadata

task_categories:
  - text-classification
language:
  - en
pretty_name: ideaset
size_categories:
  - n<1K
tags:
  - NLP
  - Reddit
  - Human-Language
  - text
license: unknown

Dataset Card for ideaset

Dataset Summary

The ideaset is a special dataset that was handpicked from a variety of Reddit communities, focusing on creative and innovative ideas. The data was collected from subreddits like r/Lifehacks, r/Idea, r/Lightbulb, and r/Business_Ideas, among others. This dataset can be used to train large language models (LLMs) to understand, generate, and assess creative ideas. It includes annotations for the relevance, clarity, and creativity level of each idea, rated on a scale from 1 to 7.

The dataset does not contain any personally identifiable information (PII) and was collected in alignment with Reddit's API guidelines. It provides valuable data for tasks like creativity assessment, innovation generation, and idea filtering.

Data Collection Process

The data was collected using Reddit’s official API, focusing on posts from subreddits that often discuss ideas or suggestions. We used posts from the following subreddits and more:

r/Lifehacks
r/Idea
r/Lightbulb
r/Business_Ideas
r/TravelIdeas

All posts were scraped according to Reddit's API guidelines, ensuring that data was collected ethically and appropriately.

Annotations and Labeling Process

The dataset was annotated by a team of 3-5 annotators, following specific guidelines provided by our team. The annotations included the following tasks:

Relevance and Clarity: Each post was labeled for relevance and clarity of the idea.
Creativity Score: Each idea was assigned a creativity score on a scale from 1 to 7, where 1 indicates low creativity and 7 indicates high creativity.

To ensure high-quality labels, the annotations were verified by an independent team. Both the raw posts and their corresponding labels are available in the dataset.

Dataset Structure

The dataset consists of the following fields:

split: Indicates the dataset split, which can be one of train, val (validation), or test.
text: The full text of the Reddit post, representing an idea or suggestion.
example_id: A unique identifier for each example in the dataset.
label_objective_task: A list of two binary values. The first value represents relevance (1 = relevant, 0 = not relevant), and the second value represents clarity (1 = clear, 0 = unclear).
label_creativity: A numeric score between 1 and 7, representing the creativity level of the idea (1 = low creativity, 7 = high creativity).

Use Cases

The ideaset dataset is suited for a range of applications. Some of them may be:

Creativity Analysis: Training models to evaluate the creativity of text-based ideas.
Idea Generation: Helping LLMs generate more creative suggestions or solutions.
Innovation Filtering: Developing tools to filter and rank user-generated ideas based on clarity and creativity.
Creativity Research: The dataset can be used to analyze creativity patterns in human discourse.

Limitations

While the dataset is a valuable resource, it has certain limitations:

Subjective Labels: Creativity is subjective, and the scores may change depending on the annotators' perception.
Subset Focus: The dataset is limited to specific subreddits, which may not represent all creative communities or domains.
English-Only Content: The dataset only includes English-language posts, which may limit its applicability in non-English contexts.

Ethical Considerations

Data Privacy: The dataset does not contain any personal information about Reddit users. All data was collected from publicly available posts, adhering to Reddit’s API usage policies.
Responsible Use: This dataset is intended for research and development purposes, with a focus on advancing creativity in AI. It should not be used to generate harmful or misleading content.

Citation

If you use ideaset in your research or applications, please cite it as follows:

@dataset{ideaset2024,
  title={ideaset: A Dataset of Ideas from Reddit},
  author={Yonatan Sabag, Amit Frechter, Michael Fishman},
  year={2024},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/yonatan7/ideaset}},
}

By citing this dataset, you help support future work in creativity research and the development of language models trained on user-generated ideas.