Details
| Original language | English |
|---|---|
| Title of host publication | CIKM 2023 |
| Subtitle of host publication | Proceedings of the 32nd ACM International Conference on Information and Knowledge Management |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 5263-5266 |
| Number of pages | 4 |
| ISBN (electronic) | 9798400701245 |
| Publication status | Published - 21 Oct 2023 |
| Event | 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023 - Birmingham, United Kingdom (UK) Duration: 21 Oct 2023 → 25 Oct 2023 |
Abstract
Multimodal human understanding and analysis is an emerging research area that cuts through several disciplines like Computer Vision (CV), Natural Language Processing (NLP), Speech Processing, Human-Computer Interaction (HCI), and Multimedia. Several multimodal learning techniques have recently shown the benefit of combining multiple modalities in image-text, audio-visual and video representation learning and various downstream multimodal tasks. At the core, these methods focus on modelling the modalities and their complex interactions by using large amounts of data, different loss functions and deep neural network architectures. However, for many Web and Social media applications, there is the need to model the human, including the understanding of human behaviour and perception. For this, it becomes important to consider interdisciplinary approaches, including social sciences, semiotics and psychology. The core is understanding various cross-modal relations, quantifying bias such as social biases, and the applicability of models to real-world problems. Interdisciplinary theories such as semiotics or gestalt psychology can provide additional insights and analysis on perceptual understanding through signs and symbols via multiple modalities. In general, these theories provide a compelling view of multimodality and perception that can further expand computational research and multimedia applications on the Web and Social media. The theme of the MUWS workshop, multimodal human understanding, includes various interdisciplinary challenges related to social bias analyses, multimodal representation learning, detection of human impressions or sentiment, hate speech, sarcasm in multimodal data, multimodal rhetoric and semantics, and related topics. The MUWS workshop will be an interactive event and include keynotes by relevant experts, poster and demo sessions, research presentations and discussion.
Keywords
- human understanding, image-text relations, machine learning, multimodality, semiotics, social media, web
ASJC Scopus subject areas
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
CIKM 2023 : Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. Association for Computing Machinery (ACM), 2023. p. 5263-5266.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - MUWS'2023
T2 - 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023
AU - Cheema, Gullal S.
AU - Kastner, Marc A.
AU - Hakimov, Sherzod
AU - Garcia, Noa
N1 - Funding Information: The MUWS 2023 workshop is co-organised by members who received funding from the German Federal Ministry of Education and Research (BMBF, FakeNarratives project, no. 16KIS1517).
PY - 2023/10/21
Y1 - 2023/10/21
N2 - Multimodal human understanding and analysis is an emerging research area that cuts through several disciplines like Computer Vision (CV), Natural Language Processing (NLP), Speech Processing, Human-Computer Interaction (HCI), and Multimedia. Several multimodal learning techniques have recently shown the benefit of combining multiple modalities in image-text, audio-visual and video representation learning and various downstream multimodal tasks. At the core, these methods focus on modelling the modalities and their complex interactions by using large amounts of data, different loss functions and deep neural network architectures. However, for many Web and Social media applications, there is the need to model the human, including the understanding of human behaviour and perception. For this, it becomes important to consider interdisciplinary approaches, including social sciences, semiotics and psychology. The core is understanding various cross-modal relations, quantifying bias such as social biases, and the applicability of models to real-world problems. Interdisciplinary theories such as semiotics or gestalt psychology can provide additional insights and analysis on perceptual understanding through signs and symbols via multiple modalities. In general, these theories provide a compelling view of multimodality and perception that can further expand computational research and multimedia applications on the Web and Social media. The theme of the MUWS workshop, multimodal human understanding, includes various interdisciplinary challenges related to social bias analyses, multimodal representation learning, detection of human impressions or sentiment, hate speech, sarcasm in multimodal data, multimodal rhetoric and semantics, and related topics. The MUWS workshop will be an interactive event and include keynotes by relevant experts, poster and demo sessions, research presentations and discussion.
AB - Multimodal human understanding and analysis is an emerging research area that cuts through several disciplines like Computer Vision (CV), Natural Language Processing (NLP), Speech Processing, Human-Computer Interaction (HCI), and Multimedia. Several multimodal learning techniques have recently shown the benefit of combining multiple modalities in image-text, audio-visual and video representation learning and various downstream multimodal tasks. At the core, these methods focus on modelling the modalities and their complex interactions by using large amounts of data, different loss functions and deep neural network architectures. However, for many Web and Social media applications, there is the need to model the human, including the understanding of human behaviour and perception. For this, it becomes important to consider interdisciplinary approaches, including social sciences, semiotics and psychology. The core is understanding various cross-modal relations, quantifying bias such as social biases, and the applicability of models to real-world problems. Interdisciplinary theories such as semiotics or gestalt psychology can provide additional insights and analysis on perceptual understanding through signs and symbols via multiple modalities. In general, these theories provide a compelling view of multimodality and perception that can further expand computational research and multimedia applications on the Web and Social media. The theme of the MUWS workshop, multimodal human understanding, includes various interdisciplinary challenges related to social bias analyses, multimodal representation learning, detection of human impressions or sentiment, hate speech, sarcasm in multimodal data, multimodal rhetoric and semantics, and related topics. The MUWS workshop will be an interactive event and include keynotes by relevant experts, poster and demo sessions, research presentations and discussion.
KW - human understanding
KW - image-text relations
KW - machine learning
KW - multimodality
KW - semiotics
KW - social media
KW - web
UR - http://www.scopus.com/inward/record.url?scp=85178153385&partnerID=8YFLogxK
U2 - 10.1145/3583780.3615310
DO - 10.1145/3583780.3615310
M3 - Conference contribution
AN - SCOPUS:85178153385
SP - 5263
EP - 5266
BT - CIKM 2023
PB - Association for Computing Machinery (ACM)
Y2 - 21 October 2023 through 25 October 2023
ER -