gtfintechlab/SubjECTive-QA

Dataset Summary

For dataset summary, please refer to https://huggingface.co/datasets/gtfintechlab/subjectiveqa

Additional Information

This dataset is annotated across six subjective dimensions: Assertive, Cautious, Optimistic, Specific, Clear, and Relevant. It contains 2,747 longform QA pairs taken from the Earnings Call Transcripts of 120 companies listed on the NYSE from 2007-2021.

Label Interpretation (e.g. CLEAR)

• 0: Negatively Demonstrative of the dimension (e.g. CLEAR)
  Indicates that the response lacks clarity.

• 1: Neutral Demonstration of 'the dimension (e.g. CLEAR)
  Indicates that the response has an average level of clarity.

• 2: Positively Demonstrative of the dimension (e.g. CLEAR)
  Indicates that the response is clear and transparent.

Licensing Information

The SubjECTive-QA dataset is licensed under the Creative Commons Attribution 4.0 International License. More information in the paper.

Citation Information

@misc{pardawala2024subjectiveqameasuringsubjectivityearnings,
      title={SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysis}, 
      author={Huzaifa Pardawala and Siddhant Sukhani and Agam Shah and Veer Kejriwal and Abhishek Pillai and Rohan Bhasin and Andrew DiBiasio and Tarun Mandapati and Dhruv Adha and Sudheer Chava},
      year={2024},
      eprint={2410.20651},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2410.20651}, 
}

Contact

Please contact Huzaifa Pardawala (huzaifahp7[at]gatech[dot]edu) or Agam Shah (ashah482[at]gatech[dot]edu) about any SubjECTive-QA related issues and questions.

GitHub Link

Link to our GitHub repository.