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Understanding and classifying image tweets

Authors:

Tao Chen,

Dongyuan Lu,

Min-Yen Kan,

Peng CuiAuthors Info & Claims

MM '13: Proceedings of the 21st ACM international conference on Multimedia

Pages 781 - 784

https://doi.org/10.1145/2502081.2502203

Published: 21 October 2013 Publication History

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Abstract

Social media platforms now allow users to share images alongside their textual posts. These image tweets make up a fast-growing percentage of tweets, but have not been studied in depth unlike their text-only counterparts. We study a large corpus of image tweets in order to uncover what people post about and the correlation between the tweet's image and its text. We show that an important functional distinction is between visually-relevant and visually-irrelevant tweets, and that we can successfully build an automated classifier utilizing text, image and social context features to distinguish these two classes, obtaining a macro F1 of 70.5%.

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Cited By

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Alam FAlam TOfli FImran M(2024)Robust Training of Social Media Image Classification ModelsIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.323083911:1(546-565)Online publication date: Feb-2024
https://doi.org/10.1109/TCSS.2022.3230839
Xu NWang JTian YZhang RMao W(2023)AnANet: Association and Alignment Network for Modeling Implicit Relevance in Cross-Modal Correlation ClassificationIEEE Transactions on Multimedia10.1109/TMM.2022.322996025(7867-7880)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/TMM.2022.3229960
Gupta TRoy S(2023)Handcrafted Features Based Analysis of Social Media Images for Disaster Response2023 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)10.1109/ICT-DM58371.2023.10286923(1-6)Online publication date: 13-Sep-2023
https://doi.org/10.1109/ICT-DM58371.2023.10286923
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Index Terms

Understanding and classifying image tweets
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Information & Contributors

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Published In

MM '13: Proceedings of the 21st ACM international conference on Multimedia

October 2013

1166 pages

ISBN:9781450324045

DOI:10.1145/2502081

General Chairs:
Alejandro (Alex) Jaimes
Yahoo!, Spain
,
Nicu Sebe
University of Trento, Italy
,
Nozha Boujemaa
INRIA, France
,
Program Chairs:
Daniel Gatica-Perez
IDIAP & EPFL, Switzerland
,
David A. Shamma
Yahoo!, USA
,
Marcel Worring
University of Amsterdam, The Netherlands
,
Roger Zimmermann
National University of Singapore, Singapore

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 October 2013

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MM '13: ACM Multimedia Conference

October 21 - 25, 2013

Barcelona, Spain

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MM '13 Paper Acceptance Rate 47 of 235 submissions, 20%;

Overall Acceptance Rate 995 of 4,171 submissions, 24%

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The 32nd ACM International Conference on Multimedia

October 28 - November 1, 2024

Melbourne , VIC , Australia

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Cited By

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Alam FAlam TOfli FImran M(2024)Robust Training of Social Media Image Classification ModelsIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.323083911:1(546-565)Online publication date: Feb-2024
https://doi.org/10.1109/TCSS.2022.3230839
Xu NWang JTian YZhang RMao W(2023)AnANet: Association and Alignment Network for Modeling Implicit Relevance in Cross-Modal Correlation ClassificationIEEE Transactions on Multimedia10.1109/TMM.2022.322996025(7867-7880)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/TMM.2022.3229960
Gupta TRoy S(2023)Handcrafted Features Based Analysis of Social Media Images for Disaster Response2023 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)10.1109/ICT-DM58371.2023.10286923(1-6)Online publication date: 13-Sep-2023
https://doi.org/10.1109/ICT-DM58371.2023.10286923
Sun LLi QLiu LSu Y(2023)Unsupervised multimodal learning for image-text relation classification in tweetsPattern Analysis and Applications10.1007/s10044-023-01204-526:4(1793-1804)Online publication date: 10-Oct-2023
https://doi.org/10.1007/s10044-023-01204-5
Hai-Jew S(2022)Open Social-Shared Animated GIFs for Peer-to-Peer Teaching and LearningPractical Peer-to-Peer Teaching and Learning on the Social Web10.4018/978-1-7998-6496-7.ch006(194-228)Online publication date: 2022
https://doi.org/10.4018/978-1-7998-6496-7.ch006
Tao CCheung Y(2022)Social Media Mining on Taipei's Mass Rapid Transit Station Services based on Visual-Semantic Deep LearningWSEAS TRANSACTIONS ON COMPUTERS10.37394/23205.2022.21.1621(110-117)Online publication date: 31-Mar-2022
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Fahmy STaha BKarademir H(2022)Journalistic Practices on Twitter: A Comparative Visual Study on the Personalization of Conflict Reporting on Social MediaOnline Media and Global Communication10.1515/omgc-2022-00081:1(23-59)Online publication date: 14-Feb-2022
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Weber EPapadopoulos DLapedriza AOfli FImran MTorralba A(2022)Incidents1M: a Large-Scale Dataset of Images With Natural Disasters, Damage, and IncidentsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2022.3191996(1-14)Online publication date: 2022
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Sesver DGencoglu AYildiz CGunindi ZHabibi FYazici ZEkenel H(2022)VIDI: A Video Dataset of Incidents2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)10.1109/IVMSP54334.2022.9816319(1-5)Online publication date: 26-Jun-2022
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Hossain EHoque MHoque EIslam M(2022)A Deep Attentive Multimodal Learning Approach for Disaster Identification From Social Media PostsIEEE Access10.1109/ACCESS.2022.317089710(46538-46551)Online publication date: 2022
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