research-article

Identification of useful user comments in social media: a case study on flickr commons

Authors:

Bernhard Haslhofer,

Geert-Jan HoubenAuthors Info & Claims

JCDL '13: Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries

Pages 1 - 10

https://doi.org/10.1145/2467696.2467711

Published: 22 July 2013 Publication History

Abstract

Cultural institutions are increasingly opening up their repositories and contribute digital objects to social media platforms such as Flickr. In return they often receive user comments containing information that could be incorporated in their catalog records. Since judging the usefulness of a large number of user comments is a labor-intensive task, our aim is to provide automated support for filtering potentially useful social media comments on digital objects. In this paper, we discuss the notion of usefulness in the context of social media comments and compare it from end-users as well as expertusers perspectives. Then we present a machine-learning approach to automatically classify comments according to their usefulness. Our approach makes use of syntactic and semantic comment features and also considers user context. We present the results of an experiment we did on user comments received in six different Flickr Commons collections. They show that a few relatively straightforward features can be used to infer useful comments with up to 89% accuracy.

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Cited By

Yu YMcDonald D(2023)"Why do you need 400 photographs of 400 different Lockheed Constellation?": Value Expressions by Contributors and Users of Wikimedia CommonsProceedings of the ACM on Human-Computer Interaction10.1145/36100947:CSCW2(1-34)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610094
Huh MLee YChoi DKim HOh UKim J(2022)Cocomix: Utilizing Comments to Improve Non-Visual Webtoon AccessibilityProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3502081(1-18)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3502081
Schindler MDomahidi E(2021)The growing field of interdisciplinary research on user comments: A computational scoping reviewNew Media & Society10.1177/146144482199449123:8(2474-2492)Online publication date: 15-Apr-2021
https://doi.org/10.1177/1461444821994491
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Index Terms

Identification of useful user comments in social media: a case study on flickr commons
1. Information systems
  1. Information retrieval
  2. Information storage systems

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Published In

cover image ACM Conferences

JCDL '13: Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries

July 2013

480 pages

ISBN:9781450320771

DOI:10.1145/2467696

General Chairs:
J. Stephen Downie
University of Illinois at Urbana-Champaign, USA
,
Robert H. McDonald
Indiana University Bloomington, USA
,
Program Chairs:
Timothy W. Cole
University of Illinois at Urbana-Champaign, USA
,
Robert Sanderson
Los Alamos National Laboratory, USA
,
Frank Shipman
Texas A&M University, USA

Copyright © 2013 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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Publication History

Published: 22 July 2013

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JCDL '13

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JCDL '13: 13th ACM/IEEE-CS Joint Conference on Digital Libraries

July 22 - 26, 2013

Indiana, Indianapolis, USA

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JCDL '13 Paper Acceptance Rate 28 of 95 submissions, 29%;

Overall Acceptance Rate 415 of 1,482 submissions, 28%

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Cited By

Yu YMcDonald D(2023)"Why do you need 400 photographs of 400 different Lockheed Constellation?": Value Expressions by Contributors and Users of Wikimedia CommonsProceedings of the ACM on Human-Computer Interaction10.1145/36100947:CSCW2(1-34)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610094
Huh MLee YChoi DKim HOh UKim J(2022)Cocomix: Utilizing Comments to Improve Non-Visual Webtoon AccessibilityProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3502081(1-18)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3502081
Schindler MDomahidi E(2021)The growing field of interdisciplinary research on user comments: A computational scoping reviewNew Media & Society10.1177/146144482199449123:8(2474-2492)Online publication date: 15-Apr-2021
https://doi.org/10.1177/1461444821994491
Aramburu MBerlanga RLanza I(2020)Social Media Multidimensional Analysis for Intelligent Health SurveillanceInternational Journal of Environmental Research and Public Health10.3390/ijerph1707228917:7(2289)Online publication date: 28-Mar-2020
https://doi.org/10.3390/ijerph17072289
Rörden JGruber DKrickl MHaslhofer B(2020)Identifying Historical Travelogues in Large Text Corpora Using Machine LearningSustainable Digital Communities10.1007/978-3-030-43687-2_67(801-815)Online publication date: 19-Mar-2020
https://doi.org/10.1007/978-3-030-43687-2_67
WANG XZHANG BHUANG MCHANG FZHOU Z(2019)Improved LDA Model for Credibility Evaluation of Online Product ReviewsIEICE Transactions on Information and Systems10.1587/transinf.2018EDP7243E102.D:11(2148-2158)Online publication date: 1-Nov-2019
https://doi.org/10.1587/transinf.2018EDP7243
Yahav IShehory OSchwartz D(2019)Comments Mining With TF-IDFIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.284012731:3(437-450)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1109/TKDE.2018.2840127
Berlanga RLanza-Cruz IAramburu M(2019)Quality Indicators for Social Business Intelligence2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS)10.1109/SNAMS.2019.8931862(229-236)Online publication date: Oct-2019
https://doi.org/10.1109/SNAMS.2019.8931862
Kaur HPannu HMalhi A(2019)Multimedia blog volume prediction using adaptive neuro fuzzy inference system and evolutionary algorithmsMultimedia Tools and Applications10.1007/s11042-019-07903-878:22(31673-31707)Online publication date: 24-Jul-2019
https://doi.org/10.1007/s11042-019-07903-8
Le LShah CChoi E(2019)Assessing the quality of answers autonomously in community question–answeringInternational Journal on Digital Libraries10.1007/s00799-019-00272-520:4(351-367)Online publication date: 5-Aug-2019
https://doi.org/10.1007/s00799-019-00272-5
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