Traditional research on different forms of media analysis has been primarily focused on the low and mid-level tasks, such as indexing and summarization. With the availability of big data and powerful learning techniques, the human factors in media, such as the affective content, insight generation, societal impact and trends. The second workshop on Media Analytics for Societal Trends (MAST) comes at a critical time when interest in human-centric media analytics is on the rise. MAST aims to bring together researchers and professionals working in fields ranging from multimedia computing, multimodal signal processing to social science, with the goal to understand different computational tools and methodologies for systematic study of affect in media and the various aspects of impact media has on viewers, users and content creators. The scientific program of ICMI MAST will include plenary talks, poster sessions and panel discussions. To this end, we solicit original research papers related (but not limited) to the topics listed below.
- Affect and sentiment analysis from media, single and multimodal (e.g. emotional appeal, persuasiveness, emotion perception and communication)
- Impact prediction and analysis (e.g. popularity, virality, memorability, commercial success and influence of media content on society)
- Human-media interaction
- Media analytics and methodologies (e.g. automated discovery of rich analytics related to gender, profession, ethnicity, personality, stereotypes, topics of discussion/conversation, and analysis of their relationships and dynamics)
- Large-scale media data collection, annotation and benchmarking.
The first Media Analytics for Societal Trends workshop was organized in 2018 at San Diego in conjunction with the International Conference of Multimedia and Expo (ICME). The workshop brought together engineers and computer scientists from academia and industry with social scientists and media experts. The workshop attracted a large audience and showcased cutting edge research on different aspects of media analytics with an attempt to understand its impact on different societal patterns. The speakers and panels addressed the open challenges and future directions of computational media intelligence.
Multimedia content is omnipresent. Media permeates our daily routines and influences what we know, how we think and communicate ideas and opinions. The stories being told by media cover a wide range of domains. These include entertainment (movies, television, games, "user-generated" stories e.g., on YouTube), commerce (advertisements, trailers), education (lectures, documentaries, data archives), and information sharing (news: online, broadcast radio and TV, print).
Multimedia is a rich field for studying interactions at different scales: how different modalities of the content (i.e., video, audio and language use) interact with each other to provide rich storytelling; how the content in the movies and videos convey message to the viewers, and how it influences the viewers' perception; and how viewers and consumers interact with the media content: proximally (e.g., movie ratings, box office ratings), perceptually (affect, user reaction, perceived sentiment) and long-term (e.g., influence of movie on portrayal on certain stereotypes)
Media is said to also mirror the society we live in, but the reverse is often equally true. Research in different forms of media processing have been around for a while, but they have usually only focused on the low and mid-level tasks, such as indexing, summarization, without making an attempt to close the loop with any impact metrics on the audience. With the advent of big data processing, however, the field of computational media research is now gaining steam, and significant efforts are being put to study the affective content, societal impact and trends in media data. We believe that this workshop comes at a critical time when interest in human-centric media analytics is on the rise.
The workshop will include poster presentations for submitted papers, invited talks and panel discussions. Paper submission can be 4-6 pages with an extra page for references.
Paper review procedure will be double blind and will be organized via EasyChair. No additional publication is planned other than the standard ACM submission. We will ensure that each paper receive at least 2 reviews from our PC members who will be experts in this area.
- Abstract submission deadline : July 22, 2019
- Notification of acceptance : August 19, 2019
- Camera ready version due : Sept. 16, 2019
- Workshop date : TBD
- Naveen Kumar, Disney Research (Contact)
- Tanaya Guha, University of Warwick
- Jeremy Lee , NTHU Taiwan
- Ming Li , Duke Kunshan Univerity
- Shri Narayanan, USC
- Krishna Somandepalli, USC