arXiv:2402.18702v1 Announce Type: new
Abstract: This study aims to investigate the comprehensive characterization of information content in multimedia (videos), particularly on YouTube. The research presents a multi-method framework for characterizing multimedia content by clustering signals from various modalities, such as audio, video, and text. With a focus on South China Sea videos as a case study, this approach aims to enhance our understanding of online content, especially on YouTube. The dataset includes 160 videos, and our findings offer insights into content themes and patterns within different modalities of a video based on clusters. Text modality analysis revealed topical themes related to geopolitical countries, strategies, and global security, while video and audio modality analysis identified distinct patterns of signals related to diverse sets of videos, including news analysis/reporting, educational content, and interviews. Furthermore, our findings uncover instances of content repurposing within video clusters, which were identified using the barcode technique and audio similarity assessments. These findings indicate potential content amplification techniques. In conclusion, this study uniquely enhances our current understanding of multimedia content information based on modality clustering techniques.
Enhancing Understanding of Multimedia Content through Modality Clustering
As the internet continues to evolve, multimedia content has become an integral part of our daily digital experience. Platforms like YouTube have contributed significantly to the growth of multimedia content, with millions of videos being uploaded and consumed every day. However, understanding the information within these videos can be challenging due to their diverse nature.
This study addresses this challenge by presenting a multi-method framework for characterizing multimedia content on YouTube. By clustering signals from different modalities, such as audio, video, and text, the researchers aim to provide a comprehensive characterization of the information present in videos.
The multi-disciplinary nature of this research is evident in the approach taken. By analyzing different modalities, the study combines techniques from fields such as audio signal processing, computer vision, and natural language processing. This integration of multiple disciplines enhances the accuracy and depth of the analysis.
The case study conducted on South China Sea videos demonstrates the effectiveness of the proposed framework. By analyzing a dataset of 160 videos, the researchers were able to gain insights into content themes and patterns. The analysis of the text modality revealed geopolitical themes related to countries, strategies, and global security. On the other hand, the analysis of video and audio modalities identified distinct patterns related to news analysis/reporting, education, and interviews.
One interesting finding of this study is the discovery of content repurposing within video clusters. The researchers used techniques such as the barcode technique and audio similarity assessments to identify instances of content amplification. This insight into content repurposing highlights the potential for future research on content manipulation techniques and their impact on the dissemination of information through multimedia platforms.
The implications of this research go beyond the specific case study of South China Sea videos. The framework presented in this study can be applied to other domains and topics, allowing for a deeper understanding of multimedia content on various platforms. Whether it’s analyzing animations, artificial reality, augmented reality, or virtual realities, the multi-method framework can provide valuable insights into the information contained within these multimedia experiences.
Overall, this study contributes to the wider field of multimedia information systems by introducing a comprehensive characterization framework for multimedia content on YouTube. By combining signals from different modalities, the researchers provide a multi-faceted analysis that enriches our understanding of online content. The findings of this study have significant implications for content creators, platform administrators, and researchers interested in studying the impact of multimedia content on society.