Analyzing clarification in asynchronous information‐seeking conversations
Leila Tavakoli,
Hamed Zamani,
Falk Scholer,
William Bruce Croft and
Mark Sanderson
Journal of the Association for Information Science & Technology, 2022, vol. 73, issue 3, 449-471
Abstract:
This research analyzes human‐generated clarification questions to provide insights into how they are used to disambiguate and provide a better understanding of information needs. A set of clarification questions is extracted from posts on the Stack Exchange platform. Novel taxonomy is defined for the annotation of the questions and their responses. We investigate the clarification questions in terms of whether they add any information to the post (the initial question posted by the asker) and the accepted answer, which is the answer chosen by the asker. After identifying, which clarification questions are more useful, we investigated the characteristics of these questions in terms of their types and patterns. Non‐useful clarification questions are identified, and their patterns are compared with useful clarifications. Our analysis indicates that the most useful clarification questions have similar patterns, regardless of topic. This research contributes to an understanding of clarification in conversations and can provide insight for clarification dialogues in conversational search scenarios and for the possible system generation of clarification requests in information‐seeking conversations.
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1002/asi.24562
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:73:y:2022:i:3:p:449-471
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=2330-1635
Access Statistics for this article
More articles in Journal of the Association for Information Science & Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().