Quantising contribution effort in online communities

Grégoire Burel; Yulan He

doi:10.1145/2567948.2576949

Quantising contribution effort in online communities

Grégoire Burel, Yulan He

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

We describe the Joint Effort-Topic (JET) model and the Author Joint Effort-Topic (aJET) model that estimate the effort required for users to contribute on different topics. We propose to learn word-level effort taking into account term preference over time and use it to set the priors of our models. Since there is no gold standard which can be easily built, we evaluate them by measuring their abilities to validate expected behaviours such as correlations between user contributions and the associated effort.

Original language	English
Title of host publication	WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
Place of Publication	New York, NY (US)
Publisher	ACM
Pages	549-550
Number of pages	2
ISBN (Print)	978-1-4503-2745-9
DOIs	https://doi.org/10.1145/2567948.2576949
Publication status	Published - 7 Apr 2014
Event	23rd International Conference on World Wide Web - Seoul, Korea, Republic of Duration: 7 Apr 2014 → 11 Apr 2014

Conference

Conference	23rd International Conference on World Wide Web
Abbreviated title	WWW 2014
Country/Territory	Korea, Republic of
City	Seoul
Period	7/04/14 → 11/04/14

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10.1145/2567948.2576949

Cite this

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title = "Quantising contribution effort in online communities",

abstract = "We describe the Joint Effort-Topic (JET) model and the Author Joint Effort-Topic (aJET) model that estimate the effort required for users to contribute on different topics. We propose to learn word-level effort taking into account term preference over time and use it to set the priors of our models. Since there is no gold standard which can be easily built, we evaluate them by measuring their abilities to validate expected behaviours such as correlations between user contributions and the associated effort.",

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year = "2014",

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booktitle = "WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web",

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T1 - Quantising contribution effort in online communities

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AU - He, Yulan

PY - 2014/4/7

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N2 - We describe the Joint Effort-Topic (JET) model and the Author Joint Effort-Topic (aJET) model that estimate the effort required for users to contribute on different topics. We propose to learn word-level effort taking into account term preference over time and use it to set the priors of our models. Since there is no gold standard which can be easily built, we evaluate them by measuring their abilities to validate expected behaviours such as correlations between user contributions and the associated effort.

AB - We describe the Joint Effort-Topic (JET) model and the Author Joint Effort-Topic (aJET) model that estimate the effort required for users to contribute on different topics. We propose to learn word-level effort taking into account term preference over time and use it to set the priors of our models. Since there is no gold standard which can be easily built, we evaluate them by measuring their abilities to validate expected behaviours such as correlations between user contributions and the associated effort.

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UR - https://dl.acm.org/citation.cfm?doid=2567948.2576949

U2 - 10.1145/2567948.2576949

DO - 10.1145/2567948.2576949

M3 - Conference publication

AN - SCOPUS:84990932248

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SP - 549

EP - 550

BT - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web

PB - ACM

CY - New York, NY (US)

T2 - 23rd International Conference on World Wide Web

Y2 - 7 April 2014 through 11 April 2014

ER -

Quantising contribution effort in online communities

Abstract

Conference

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