Welcome to the SIGMM Community Discussion Column! In this very first edition we would like to introduce the column to the community, its objectives and main operative characteristics.
Given the exponential amount of multimedia data shared online and offline everyday, research in Multimedia is of unprecedented importance. We might be now facing a new era of our research field, and we would like the whole community to be involved in the improvement and evolution of our domain.
The column has two main goals. First, we will promote dialogue regarding topics of interests for the MM community, by providing tools for continuous discussion among the members of the multimedia community. Every quarter, we will discuss (usually) one topic via online tools. Topics will include “What is Multimedia, and what is the role of the Multimedia community in science?”; “Diversity and minorities in the community”; “The ACM code of ethics”; etc.
Second, we will monitor and summarize on-going discussions, and spread their results within and outside the community. Every edition of this column will then summarize the discussion, highlighting popular and non-popular opinions, agreed action points and future work.
To foster the discussion, we set up an online discussion forum to which all members of the multimedia community (expertise and seniority mixed) can participate: the Facebook MM Community Discussion group (follow this link: https://www.facebook.com/groups/132278853988735/) . For every edition of the column, we will choose an initial set of topics of high relevance for the community. We will include, for example, topics that have been previously discussed at ACM meetings (e.g., the code of ethics), or in related events (e.g., Diversity at MM Women lunch), or popular off-line discussions among MM researchers (e.g., review processes, vision of the scientific community…). In the first 15 days of the quarter, the members of the community will choose one topic from this short-list via an online poll shared through the MM Facebook group. We will then select the topic that received the higher number of votes as the subject for the quarterly discussion.
Volunteers or selected members of the MM group will start the discussion via Facebook posts on the group page. The discussion will be then open for a period of a month. All members of the community can participate by replying to posts or by directly posting on the group page, describing their point of view on the subject while being concise and clear. During this period, we will monitor and moderate (when needed) the discussion. At the end of the month, we will summarise the discussion by describing its evolution, exposing major and minor opinions, outlining highlights and lowlights. A final text with the summary and some relevant discussion extracts will be prepared and will appear in the SIGMM Records and in the Facebook “MM Community page”: https://www.facebook.com/MM-Community-217668705388738/.
Hopefully, the community will benefit from this initiative by either reaching some consensus or by pointing out important topics that are not mature enough and require further exploration. In the long-term, we hope these process will make the community evolve through large consensus and bottom-up discussions.
Let’s contribute and foster research around topics of high interest for the community!
Xavi and Miriam
Dr. Xavier Alameda-Pineda (Xavi) is research scientist at INRIA. Xavi’s interdisciplinary background (Msc in Mathematics, Telecommunications and Computer Science) grounded him to pursue his PhD in Mathematics and Computer Science, and a further post-doc in the University of Trento. His research interests are signal processing, computer vision and machine learning for scene and behavior understanding using multimodal data. He is the winner of the best paper award of ACM MM 2015, the best student paper award at IEEE WASPAA 2015 and the best scientific paper award at IAPR ICPR 2016.
Dr. Miriam Redi is a research scientist in the Social Dynamics team at Bell Labs Cambridge. Her research focuses on content-based social multimedia understanding and culture analytics. In particular, Miriam explores ways to automatically assess visual aesthetics, sentiment, and creativity and exploit the power of computer vision in the context of web, social media, and online communities. Previously, she was a postdoc in the Social Media group at Yahoo Labs Barcelona and a research scientist at Yahoo London. Miriam holds a PhD from the Multimedia group in EURECOM, Sophia Antipolis.