Details
| Original language | English |
|---|---|
| Title of host publication | CHIIR 2020 |
| Subtitle of host publication | Proceedings of the 2020 Conference on Human Information Interaction and Retrieval |
| Place of Publication | New York |
| Pages | 53-62 |
| Number of pages | 10 |
| Publication status | Published - Mar 2020 |
| Externally published | Yes |
| Event | CHIIR 2020: ACM SIGIR Conference on Human Information Interaction and Retrieval - Vancouver, Canada Duration: 14 Mar 2020 → 18 Mar 2020 |
Abstract
Millions of arguments are shared on the web. Future information systems will be able to exploit this valuable knowledge source and to retrieve arguments relevant and convincing to our specific need - -all with an interface as intuitive as asking your friend "Why ...". Although recent advancements in argument mining, conversational search, and voice recognition have put such systems within reach, many questions remain open, especially on the interface side. In this regard the paper at hand presents the first study of argument search behavior. We conduct an online-survey and a focused user study, putting emphasis on what people expect argument search to be like, rather than on what current first-generation systems provide. Our participants expected to use voice-based argument search mostly at home, but also together with others. Moreover, they expect such search systems to provide rich information on retrieved arguments, such as the source, supporting evidence, and background knowledge on entities or events mentioned. In observed interactions with a simulated system we found that the participants adapted their search behavior to different types of tasks, and that up-front categorization of the retrieved arguments is perceived as helpful if this is short. Our findings are directly applicable to the design of argument search systems, not only voice-based ones.
Keywords
- Argument search, Conversational search, Online survey, User study, Voice-based search
ASJC Scopus subject areas
- Computer Science(all)
- Human-Computer Interaction
- Computer Science(all)
- Information Systems
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CHIIR 2020: Proceedings of the 2020 Conference on Human Information Interaction and Retrieval. New York, 2020. p. 53-62.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Investigating Expectations for Voice-based and Conversational Argument Search on the Web
AU - Kiesel, Johannes
AU - Lang, Kevin
AU - Wachsmuth, Henning
AU - Hornecker, Eva
AU - Stein, Benno
PY - 2020/3
Y1 - 2020/3
N2 - Millions of arguments are shared on the web. Future information systems will be able to exploit this valuable knowledge source and to retrieve arguments relevant and convincing to our specific need - -all with an interface as intuitive as asking your friend "Why ...". Although recent advancements in argument mining, conversational search, and voice recognition have put such systems within reach, many questions remain open, especially on the interface side. In this regard the paper at hand presents the first study of argument search behavior. We conduct an online-survey and a focused user study, putting emphasis on what people expect argument search to be like, rather than on what current first-generation systems provide. Our participants expected to use voice-based argument search mostly at home, but also together with others. Moreover, they expect such search systems to provide rich information on retrieved arguments, such as the source, supporting evidence, and background knowledge on entities or events mentioned. In observed interactions with a simulated system we found that the participants adapted their search behavior to different types of tasks, and that up-front categorization of the retrieved arguments is perceived as helpful if this is short. Our findings are directly applicable to the design of argument search systems, not only voice-based ones.
AB - Millions of arguments are shared on the web. Future information systems will be able to exploit this valuable knowledge source and to retrieve arguments relevant and convincing to our specific need - -all with an interface as intuitive as asking your friend "Why ...". Although recent advancements in argument mining, conversational search, and voice recognition have put such systems within reach, many questions remain open, especially on the interface side. In this regard the paper at hand presents the first study of argument search behavior. We conduct an online-survey and a focused user study, putting emphasis on what people expect argument search to be like, rather than on what current first-generation systems provide. Our participants expected to use voice-based argument search mostly at home, but also together with others. Moreover, they expect such search systems to provide rich information on retrieved arguments, such as the source, supporting evidence, and background knowledge on entities or events mentioned. In observed interactions with a simulated system we found that the participants adapted their search behavior to different types of tasks, and that up-front categorization of the retrieved arguments is perceived as helpful if this is short. Our findings are directly applicable to the design of argument search systems, not only voice-based ones.
KW - Argument search
KW - Conversational search
KW - Online survey
KW - User study
KW - Voice-based search
UR - http://www.scopus.com/inward/record.url?scp=85082440273&partnerID=8YFLogxK
U2 - 10.1145/3343413.3377978
DO - 10.1145/3343413.3377978
M3 - Conference contribution
AN - SCOPUS:85082440273
SN - 9781450368926
SP - 53
EP - 62
BT - CHIIR 2020
CY - New York
T2 - CHIIR 2020
Y2 - 14 March 2020 through 18 March 2020
ER -