The Effects of System Initiative during Conversational Collaborative Search

Our research in this paper lies at the intersection of collaborative and conversational search. We report on a Wizard of Oz lab study in which 27 pairs of participants collaborated on search tasks over the Slack messaging platform. To complete tasks, pairs of collaborators interacted with a so-calle...

Full description

Saved in:
Bibliographic Details
Published inarXiv.org
Main Authors Avula, Sandeep, Choi, Bogeum, Arguello, Jaime
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 20.02.2022
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Our research in this paper lies at the intersection of collaborative and conversational search. We report on a Wizard of Oz lab study in which 27 pairs of participants collaborated on search tasks over the Slack messaging platform. To complete tasks, pairs of collaborators interacted with a so-called \emph{searchbot} with conversational capabilities. The role of the searchbot was played by a reference librarian. It is widely accepted that conversational search systems should be able to engage in \emph{mixed-initiative interaction} -- take and relinquish control of a multi-agent conversation as appropriate. Research in discourse analysis differentiates between dialog- and task-level initiative. Taking \emph{dialog-level} initiative involves leading a conversation for the sole purpose of establishing mutual belief between agents. Conversely, taking \emph{task-level} initiative involves leading a conversation with the intent to influence the goals of the other agent(s). Participants in our study experienced three \emph{searchbot conditions}, which varied based on the level of initiative the human searchbot was able to take: (1) no initiative, (2) only dialog-level initiative, and (3) both dialog- and task-level initiative. We investigate the effects of the searchbot condition on six different types of outcomes: (RQ1) perceptions of the searchbot's utility, (RQ2) perceptions of workload, (RQ3) perceptions of the collaboration, (RQ4) patterns of communication and collaboration, and perceived (RQ5) benefits and (RQ6) challenges from engaging with the searchbot.
AbstractList Our research in this paper lies at the intersection of collaborative and conversational search. We report on a Wizard of Oz lab study in which 27 pairs of participants collaborated on search tasks over the Slack messaging platform. To complete tasks, pairs of collaborators interacted with a so-called \emph{searchbot} with conversational capabilities. The role of the searchbot was played by a reference librarian. It is widely accepted that conversational search systems should be able to engage in \emph{mixed-initiative interaction} -- take and relinquish control of a multi-agent conversation as appropriate. Research in discourse analysis differentiates between dialog- and task-level initiative. Taking \emph{dialog-level} initiative involves leading a conversation for the sole purpose of establishing mutual belief between agents. Conversely, taking \emph{task-level} initiative involves leading a conversation with the intent to influence the goals of the other agent(s). Participants in our study experienced three \emph{searchbot conditions}, which varied based on the level of initiative the human searchbot was able to take: (1) no initiative, (2) only dialog-level initiative, and (3) both dialog- and task-level initiative. We investigate the effects of the searchbot condition on six different types of outcomes: (RQ1) perceptions of the searchbot's utility, (RQ2) perceptions of workload, (RQ3) perceptions of the collaboration, (RQ4) patterns of communication and collaboration, and perceived (RQ5) benefits and (RQ6) challenges from engaging with the searchbot.
Proc. ACM Hum.-Comput. Interact. 6, CSCW1, Article 66 (April 2022), 30 pages Our research in this paper lies at the intersection of collaborative and conversational search. We report on a Wizard of Oz lab study in which 27 pairs of participants collaborated on search tasks over the Slack messaging platform. To complete tasks, pairs of collaborators interacted with a so-called \emph{searchbot} with conversational capabilities. The role of the searchbot was played by a reference librarian. It is widely accepted that conversational search systems should be able to engage in \emph{mixed-initiative interaction} -- take and relinquish control of a multi-agent conversation as appropriate. Research in discourse analysis differentiates between dialog- and task-level initiative. Taking \emph{dialog-level} initiative involves leading a conversation for the sole purpose of establishing mutual belief between agents. Conversely, taking \emph{task-level} initiative involves leading a conversation with the intent to influence the goals of the other agent(s). Participants in our study experienced three \emph{searchbot conditions}, which varied based on the level of initiative the human searchbot was able to take: (1) no initiative, (2) only dialog-level initiative, and (3) both dialog- and task-level initiative. We investigate the effects of the searchbot condition on six different types of outcomes: (RQ1) perceptions of the searchbot's utility, (RQ2) perceptions of workload, (RQ3) perceptions of the collaboration, (RQ4) patterns of communication and collaboration, and perceived (RQ5) benefits and (RQ6) challenges from engaging with the searchbot.
Author Choi, Bogeum
Avula, Sandeep
Arguello, Jaime
Author_xml – sequence: 1
  givenname: Sandeep
  surname: Avula
  fullname: Avula, Sandeep
– sequence: 2
  givenname: Bogeum
  surname: Choi
  fullname: Choi, Bogeum
– sequence: 3
  givenname: Jaime
  surname: Arguello
  fullname: Arguello, Jaime
BackLink https://doi.org/10.1145/3512913$$DView published paper (Access to full text may be restricted)
https://doi.org/10.48550/arXiv.2202.09728$$DView paper in arXiv
BookMark eNotj1FLwzAUhYMoOOd-gE8WfG5Nb3qb7FHK1OHAh_W9ZE3iOrpmJm1x_964-nQ5l4_D-e7IdWc7TchDSpNMINJn6X6aMQGgkNAlB3FFZsBYGosM4JYsvD9QSiHngMhm5KPc62hljK57H1kTbc--18do3TV9I_tm1JEaXNN9RYXtRu18-NlOtiG2rdxZNzFbLV29vyc3RrZeL_7vnJSvq7J4jzefb-viZRNLBIhlnSLXnO5QMMSlUUpkiqkUU66ENAyBKlA64yBrxTIMdHDhguc0D36GzcnjVHsxrU6uOUp3rv6Mq4txIJ4m4uTs96B9Xx3s4MJsX0HOUo55ToH9Aj-oWbs
ContentType Paper
Journal Article
Copyright 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
http://creativecommons.org/licenses/by/4.0
Copyright_xml – notice: 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: http://creativecommons.org/licenses/by/4.0
DBID 8FE
8FG
ABJCF
ABUWG
AFKRA
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
HCIFZ
L6V
M7S
PIMPY
PQEST
PQQKQ
PQUKI
PRINS
PTHSS
AKY
GOX
DOI 10.48550/arxiv.2202.09728
DatabaseName ProQuest SciTech Collection
ProQuest Technology Collection
Materials Science & Engineering Collection
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials
ProQuest Central
Technology Collection
ProQuest One Community College
ProQuest Central
SciTech Premium Collection (Proquest) (PQ_SDU_P3)
ProQuest Engineering Collection
ProQuest Engineering Database
Publicly Available Content Database
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
Engineering Collection
arXiv Computer Science
arXiv.org
DatabaseTitle Publicly Available Content Database
Engineering Database
Technology Collection
ProQuest Central Essentials
ProQuest One Academic Eastern Edition
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Technology Collection
ProQuest SciTech Collection
ProQuest Central China
ProQuest Central
ProQuest Engineering Collection
ProQuest One Academic UKI Edition
ProQuest Central Korea
Materials Science & Engineering Collection
ProQuest One Academic
Engineering Collection
DatabaseTitleList Publicly Available Content Database

Database_xml – sequence: 1
  dbid: GOX
  name: arXiv.org
  url: http://arxiv.org/find
  sourceTypes: Open Access Repository
– sequence: 2
  dbid: 8FG
  name: ProQuest Technology Collection
  url: https://search.proquest.com/technologycollection1
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Physics
EISSN 2331-8422
ExternalDocumentID 2202_09728
Genre Working Paper/Pre-Print
GroupedDBID 8FE
8FG
ABJCF
ABUWG
AFKRA
ALMA_UNASSIGNED_HOLDINGS
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
FRJ
HCIFZ
L6V
M7S
M~E
PIMPY
PQEST
PQQKQ
PQUKI
PRINS
PTHSS
AKY
GOX
ID FETCH-LOGICAL-a522-ac157e70b583559fdd84d3d1517d8af3520d2de472acd345157202787606550f3
IEDL.DBID BENPR
IngestDate Mon Jan 08 05:49:26 EST 2024
Thu Oct 10 18:17:34 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-a522-ac157e70b583559fdd84d3d1517d8af3520d2de472acd345157202787606550f3
OpenAccessLink https://www.proquest.com/docview/2631756602?pq-origsite=%requestingapplication%
PQID 2631756602
PQPubID 2050157
ParticipantIDs arxiv_primary_2202_09728
proquest_journals_2631756602
PublicationCentury 2000
PublicationDate 20220220
PublicationDateYYYYMMDD 2022-02-20
PublicationDate_xml – month: 02
  year: 2022
  text: 20220220
  day: 20
PublicationDecade 2020
PublicationPlace Ithaca
PublicationPlace_xml – name: Ithaca
PublicationTitle arXiv.org
PublicationYear 2022
Publisher Cornell University Library, arXiv.org
Publisher_xml – name: Cornell University Library, arXiv.org
SSID ssj0002672553
Score 1.8342668
SecondaryResourceType preprint
Snippet Our research in this paper lies at the intersection of collaborative and conversational search. We report on a Wizard of Oz lab study in which 27 pairs of...
Proc. ACM Hum.-Comput. Interact. 6, CSCW1, Article 66 (April 2022), 30 pages Our research in this paper lies at the intersection of collaborative and...
SourceID arxiv
proquest
SourceType Open Access Repository
Aggregation Database
SubjectTerms Collaboration
Computer Science - Human-Computer Interaction
Computer Science - Information Retrieval
Multiagent systems
Searching
Verbal communication
SummonAdditionalLinks – databaseName: arXiv.org
  dbid: GOX
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwdV3BTgMhEJ20PXkxGjWtVsPB60Y6hYU9msZaNdFLTXrbwLIkXrZmtxo_3wG26cF4JQOHGWAe8OYBcOsrUxspbFZUM5sJTSudLG1WiQI9zS86dUWC7Gu-ehfPG7kZANvXwpj25-M76QPb7g4x6GkWCvUQhoiBsvX4tkmPk1GKq7c_2BHGjE1_ttaYL5YncNwDPXafInMKg7o5gxeKCkuCwR3bepb0wtlTYPBEBW6WygbZIpDB266_qWOLQ7TIJlGEz2G9fFgvVln_nUFmCORkpppJVStuJYEeWXjntHBzRxlXOW08ASHu0NVCoancXBDOUOFignYrQgmS-_kFjJptU4-BmQJVpR1y6QuRz6xGGodOPornPqipTGAcnVB-JsWKMvinjP6ZwHTvl7KfrV2JeUARec7x8v-eV3CEgfofyrn5FEa79qu-poS8szcxKr-ZT4ml
  priority: 102
  providerName: Cornell University
Title The Effects of System Initiative during Conversational Collaborative Search
URI https://www.proquest.com/docview/2631756602
https://arxiv.org/abs/2202.09728
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV07T8MwED7RRkhsPNVCqTywhrqOEycTElUfgCgVKlK3yLFjiaWPpCAmfjtnJ6UDEkukJFaGO-de_u47gBujZC5DnvmJ6mc-j_FPx5WZr3jCDO4vzLocQHYaTd744yJc1AW3soZV7myiM9R6pWyNvMci6-miiLK79ca3U6Ps6Wo9QqMBHsNMgTbBux9OZ6-_VRYWCYyZg-o405F39WTx9f55y5hl6kyEncLuuUd_jLHzMKNj8GZynRcncJAvT-HQATNVeQZPqEdSUQyXZGVIxTBOHizmx3F2k6rRkAwsfLwo69oeGez1i2sqUPE5zEfD-WDi1wMQfIlhkS9VPxS5oFmIYVKYGK1jrgONPlroWBoMnahmOueCSaUDjpGJsKUMtG8YV4TUBBfQXK6WeQuITJhQsWY0NAmP-lnM8DuYKwkaGcu_0oaWE0K6rjguUiuf1MmnDZ2dXNJ6f5fpXhuX_7--giNmGwZsEzjtQHNbfOTX6Ma3WRca8WjcrTWGd-OXBV6fv4c_0z-euw
link.rule.ids 228,230,783,787,888,12777,21400,27937,33385,33756,43612,43817
linkProvider ProQuest
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV09T8MwED1BIwQbn2qhgAfW0NRx4mRComrV0lJVqEjdIseOJZZ-JAXx8zk7Lh2QWBMrw51z93x-9w7gQUtRiIjlfiq7uc8S_NNxZe5LllKN-wtPXZYgO42H7-xlES1cwa1ytMpdTLSBWq2kqZF3aGwyXRwH9Gm98c3UKHO76kZoHIJnpKrw8OU996ezt98qC405Yuawvs604l0dUX5_fD1SapQ6U26msHv20Z9gbDPM4BS8mVgX5RkcFMtzOLLETFldwBj9SGqJ4YqsNKkVxsnIcH6sZjepGw1Jz9DHy8rV9khv719cU5OKL2E-6M97Q98NQPAFwiJfyG7ECx7kEcKkKNVKJUyFCnM0V4nQCJ0CRVXBOBVShQyRCTelDIxviCuiQIdX0FiulkUTiEgpl4miQaRTFnfzhOJ38KzEg1gb_ZUWNK0RsnWtcZEZ-2TWPi1o7-ySuf1dZXtvXP__-h6Oh_PXSTYZTcc3cEJN84BpCA_a0NiWn8UtpvRtfuf89gNS6Z6P
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=The+Effects+of+System+Initiative+during+Conversational+Collaborative+Search&rft.jtitle=arXiv.org&rft.au=Avula%2C+Sandeep&rft.au=Choi%2C+Bogeum&rft.au=Arguello%2C+Jaime&rft.date=2022-02-20&rft.pub=Cornell+University+Library%2C+arXiv.org&rft.eissn=2331-8422&rft_id=info:doi/10.48550%2Farxiv.2202.09728