research-article

Find an Expert: Designing Expert Selection Interfaces for Formal Help-Giving

Author:

Sharoda A. PaulAuthors Info & Claims

CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

May 2016

Pages 3038 - 3048

https://doi.org/10.1145/2858036.2858131

Published: 07 May 2016 Publication History

Abstract

A critical aspect of formal help-giving tasks in the enterprise is finding the right expert. We built and evaluated a tool, Find an Expert, to examine what the most important expert selection criteria are for help-seekers and how to represent them in expert selection interfaces for formal help-giving tasks. We observed users' expert selection decisions and found that the diversity of topic expertise and the amount of related experience were significantly important in helping users decide which expert to contact. Through self-reported data from users, we found that in addition to expertise and experience, expert accessibility indicators, like online availability and language proficiency, were considered important criteria for selecting experts. Finally, publicly-displayed crowdsourced ratings of experts, while deemed useful indicators of expert quality by help-seekers, raised concerns for experts. We conclude with suggestions regarding the design of expert selection interfaces for formal help-giving tasks.

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Cited By

Schoegje THardman LDe Vries APieters T(2024)Improving expert search effectiveness: Comparing ways to rank and present search resultsProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638296(56-65)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638296
Han KYou WDeng HSun LSong JHu ZYi H(2024)LanT: finding experts for digital calligraphy character restorationMultimedia Tools and Applications10.1007/s11042-023-17844-y83:24(64963-64986)Online publication date: 18-Jan-2024
https://doi.org/10.1007/s11042-023-17844-y
Chen QMagnusson MBjörk J(2023)How do ideas gain legitimacy in internal crowdsourcing idea development? Exploring the effects of feedback on idea selectionInnovation10.1080/14479338.2023.220219726:3(401-432)Online publication date: 25-Apr-2023
https://doi.org/10.1080/14479338.2023.2202197
Show More Cited By

Index Terms

Find an Expert: Designing Expert Selection Interfaces for Formal Help-Giving
1. Human-centered computing
  1. Collaborative and social computing

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cover image ACM Conferences

CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

May 2016

6108 pages

ISBN:9781450333627

DOI:10.1145/2858036

General Chairs:
Jofish Kaye
Yahoo
,
Allison Druin
University of Maryland / National Park Service
,
Program Chairs:
Cliff Lampe
University of Michigan
,
Dan Morris
Microsoft
,
Juan Pablo Hourcade
University of Iowa

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Published: 07 May 2016

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CHI'16: CHI Conference on Human Factors in Computing Systems

May 7 - 12, 2016

California, San Jose, USA

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CHI '16 Paper Acceptance Rate 565 of 2,435 submissions, 23%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Schoegje THardman LDe Vries APieters T(2024)Improving expert search effectiveness: Comparing ways to rank and present search resultsProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638296(56-65)Online publication date: 10-Mar-2024
https://dl.acm.org/doi/10.1145/3627508.3638296
Han KYou WDeng HSun LSong JHu ZYi H(2024)LanT: finding experts for digital calligraphy character restorationMultimedia Tools and Applications10.1007/s11042-023-17844-y83:24(64963-64986)Online publication date: 18-Jan-2024
https://doi.org/10.1007/s11042-023-17844-y
Chen QMagnusson MBjörk J(2023)How do ideas gain legitimacy in internal crowdsourcing idea development? Exploring the effects of feedback on idea selectionInnovation10.1080/14479338.2023.220219726:3(401-432)Online publication date: 25-Apr-2023
https://doi.org/10.1080/14479338.2023.2202197
Husain OSalim NAlias RAbdelsalam SThurasamy RFaisal HHamzah M(2021)Modeling Academic Research Collaborator Selection Using an Integrated ModelIEEE Access10.1109/ACCESS.2021.30962509(102397-102421)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3096250
Kiani KChilana PBunt AGrossman TFitzmaurice G(2020)“I Would Just Ask Someone”: Learning Feature-Rich Design Software in the Modern Workplace2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)10.1109/VL/HCC50065.2020.9127288(1-10)Online publication date: Aug-2020
https://doi.org/10.1109/VL/HCC50065.2020.9127288
Husain OSalim NAlias RAbdelsalam SHassan A(2019)Expert Finding Systems: A Systematic ReviewApplied Sciences10.3390/app92042509:20(4250)Online publication date: 11-Oct-2019
https://doi.org/10.3390/app9204250
Lu DMarlow JKocielnik RAvrahami DMandryk RHancock MPerry MCox A(2018)Challenges and Opportunities for Technology-Supported Activity Reporting in the WorkplaceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3173744(1-12)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3173744

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