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Home > Proceedings / Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 1

Community Clustering: Leveraging an Academic Crowd to Form Coherent Conference Sessions

February 1, 2023

Authors

Paul André,Haoqi Zhang,Juho Kim,Lydia Chilton,Steven Dow,Robert Miller

Carnegie Mellon University,Northwestern University,Massachusetts Institute of Technology,University of Washington,Carnegie Mellon University,Massachusetts Institute of Technology


Published:

2013-11-10

Proceedings:

Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 1

Volume

Issue:

Vol. 1 (2013): First AAAI Conference on Human Computation and Crowdsourcing

Track:

Full Papers

Downloads:

Download PDF

Abstract:

Creating sessions of related papers for a large conference is a complex and time-consuming task. Traditionally, a few conference organizers group papers into sessions manually. Organizers often fail to capture the affinities between papers beyond created sessions, making incoherent sessions difficult to fix and alternative groupings hard to discover. This paper proposes committeesourcing and authorsourcing approaches to session creation (a specific instance of clustering and constraint satisfaction) that tap into the expertise and interest of committee members and authors for identifying paper affinities. During the planning of ACM CHI'13, a large conference on human-computer interaction, we recruited committee members to group papers using two online distributed clustering methods. To refine these paper affinities — and to evaluate the committeesourcing methods against existing manual and automated approaches — we recruited authors to identify papers that fit well in a session with their own. Results show that authors found papers grouped by the distributed clustering methods to be as relevant as, or more relevant than, papers suggested through the existing in-person meeting. Results also demonstrate that communitysourced results capture affinities beyond sessions and provide flexibility during scheduling.

DOI:

10.1609/hcomp.v1i1.13078


HCOMP

Vol. 1 (2013): First AAAI Conference on Human Computation and Crowdsourcing


ISBN 978-1-57735-607-3


Topics: HCOMP

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