MUWS’22: 1st International Workshop on Multimodal Understanding for the Web and Social Media
Pages 692 - 693
Abstract
The 1st International Workshop on Multimodal Understanding for the Web and Social Media (MUWS 2022) is co-located with The Web Conference (WWW) and held on the 26th of April, 20221.
Multimodal learning and analysis is an emerging research area that cuts through several disciplines like Computer Vision, Natural Language Processing (NLP), Speech Processing, and Multimedia. Recently, several multimodal learning techniques have shown the benefit of combining multiple modalities in video representation learning and downstream tasks on videos. At the core, these methods are focused on modelling the modalities and their complex interactions by using large amounts of data, different loss functions and deep neural network architectures. Although these research directions are exciting and challenging, interdisciplinary fields such as semiotics are rarely considered. Literature in semiotics provides a detailed theory and analysis on meaning creation through signs and symbols via multiple modalities. In general, it provides a compelling view of multimodality and perception that can further expand computational research and applications on the web and social media.
The goal of the interdisciplinary MUWS Workshop is to bring together researchers and practitioners from the fields of Information Retrieval, Natural Language Processing, Computer Vision, Human Computation, and Semiotics to discuss and evaluate methods and solutions for effective and efficient analytics of multimodal information present in the Web or social media. We are interested in approaches, tasks, and metrics for effectively analysing multimedia information such as image-text pairs and videos to design methodologies that jointly consider information from multiple modalities. The interdisciplinary nature of processing such multimodal data involves combining ideas and methods from the fields mentioned above. We envision the workshop as a forum for researchers and practitioners from academia and industry for original contributions and practical application on multimodal information processing, mining, retrieval, search, and management.
The workshop features advanced methods for combining visual and textual content for problems such as fake news detection, predicting reliability and popularity of news articles, generating image narrative with emotion, and injecting knowledge graph information to improve visual question answering performance.
We would like to take this opportunity to sincerely thank the authors and presenters for their inspiring contributions to the workshop. Our sincere thanks are due to the program committee members for reviewing the submissions and ensuring the high quality of our workshop program. We also thank Ichiro Ide for his keynote talk, Chiao-I Tseng and Christian Otto for their invited talks in the workshop.
We are also very grateful to the organisers of The Web Conference 2022, and particularly the Workshops Chairs, Nathalie Hernandez and Preslav Nakov, for their support with the workshop organisation.
Information & Contributors
Information
Published In

April 2022
1338 pages
ISBN:9781450391306
DOI:10.1145/3487553
Copyright © 2022 Owner/Author.
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 August 2022
Check for updates
Qualifiers
- Extended-abstract
- Research
- Refereed limited
Funding Sources
Conference
WWW '22
Sponsor:
Acceptance Rates
Overall Acceptance Rate 1,899 of 8,196 submissions, 23%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 72Total Downloads
- Downloads (Last 12 months)8
- Downloads (Last 6 weeks)0
Reflects downloads up to 17 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format