Abstract
When writing, a person may need to anticipate questions from their audience, but different social groups may ask very different types of questions. If someone is writing about a problem they want to resolve, what kind of follow-up question will a domain expert ask, and could the writer better address the expert’s information needs by rewriting their original post? In this paper, we explore the task of socially-aware question generation. We collect a data set of questions and posts from social media, including background information about the question-askers’ social groups. We find that different social groups, such as experts and novices, consistently ask different types of questions. We train several text-generation models that incorporate social information, and we find that a discrete social-representation model outperforms the text-only model when different social groups ask highly different questions from one another. Our work provides a framework for developing text generation models that can help writers anticipate the information expectations of highly different social groups.- Anthology ID:
- 2022.sigdial-1.27
- Volume:
- Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue
- Month:
- September
- Year:
- 2022
- Address:
- Edinburgh, UK
- Editors:
- Oliver Lemon, Dilek Hakkani-Tur, Junyi Jessy Li, Arash Ashrafzadeh, Daniel Hernández Garcia, Malihe Alikhani, David Vandyke, Ondřej Dušek
- Venue:
- SIGDIAL
- SIG:
- SIGDIAL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 255–269
- Language:
- URL:
- https://aclanthology.org/2022.sigdial-1.27
- DOI:
- 10.18653/v1/2022.sigdial-1.27
- Cite (ACL):
- Ian Stewart and Rada Mihalcea. 2022. How Well Do You Know Your Audience? Toward Socially-aware Question Generation. In Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 255–269, Edinburgh, UK. Association for Computational Linguistics.
- Cite (Informal):
- How Well Do You Know Your Audience? Toward Socially-aware Question Generation (Stewart & Mihalcea, SIGDIAL 2022)
- PDF:
- https://preview.aclanthology.org/corrections-2024-05/2022.sigdial-1.27.pdf