ICDM 2014 Tutorial on Social Multimedia as Sensors (by Jiebo Luo and Tao Mei)


Call for Papers

Different social networking platforms have become a ubiquitous means for information sharing and communication, especially with the ever increasing mobile device availability. As a result, increasingly rich and large-scale social multimedia data (in the form of text, image, audio, and video) are being generated and posted to different social networking and media sharing platforms such as Twitter, Facebook, Instagram, Pinterest, Flickr, Vine, and Youtube. Often the multimedia content posted in these social platforms is accompanied with user comments, tags, likes, hashtags, upvotes, and so on. Such large-scale multimedia data with rich contextual information has wide ranging practical applications such as user profiling, behavior analysis, advanced personalization and recommendation systems, marketing, etc. and offers unique research challenges that require efforts from multiple disciplines such as data mining, machine learning, image and video processing, computer vision, and information retrieval. Through this workshop, we intend to offer a common platform to multidisciplinary researchers from academia as well as industry to:

  • present recent advances in social multimedia data mining and multimedia content analysis
  • present next generation technologies for managing rich social multimedia data, with special emphasis on organizing, indexing, retrieving and mining social multimedia data
  • identify novel applications and key industry drivers

Manuscripts are solicited to address a wide range of topics in social multimedia data mining, including but not limited to the following:


·        Machine learning and data mining methods for social multimedia content

·         Personalization and recommendation algorithms based on social data

·         Social context-based media content analysis

·         Prediction and forecasting models based on social multimedia

·         User profiling across multiple social media channels

·         Event driven media creation

·         Organization, indexing and navigation of social multimedia content

·         Behaviour analysis across multiple social media networks

·         Multi-modality fusion for heterogeneous social media content

·         Large scale image, video and audio classification using social contextual cues

·         Image, video and audio recommendation in social networks

·         Social media-based advertisement

·         Social network enablement via media


Prospective authors should submit high quality, original manuscripts that have not appeared, nor are under consideration elsewhere. All workshop submissions should be formatted following the same guidelines of ICDM'14 conference papers (maximum of 10 pages, in the IEEE 2-column format). Detailed formatting instructions will be available at http://icdm2015.stonybrook.edu/submission.html. All papers will be reviewed by the Program Committee based on technical quality, relevance to workshop theme, originality, significance, and clarity. The authors can opt for a double blind review, in which case the authors should therefore avoid using identifying information in the text of the paper. All papers should be submitted through here.


To encourage attendance and attract quality submissions, we are considering a special issue of extended versions of selected papers in a suitable journal, a Best Paper cash award, and three invited keynotes from academia and industry to stimulate discussions at the workshop.



Important Dates

Submission deadline: July 20, 2015
Decision notification: September 1, 2015
Camera-ready paper due date: September 10, 2015 
Workshop date: November 14, 2015

Please submit your papers here.

Program

Keynote: Patterns of Large-Scale Attention
Mor Naaman, Cornell Tech. 



Abstract: Complaints about information overload date back to medieval times, but not until recently the competition over our attention had become so fierce. At the same time, researchers now have new opportunities to capture and model the attention we collectively pay and use this data to generate new insights and applications. I give three examples of mining attention from different domains. First, I use reading depth data for online media to show attention patterns in online media and how they are dependent on factors like device, referral source and even features of the text. Second, I use geo-tagged social media data to show how pay attention to different hyper-local locations, how this attention is spread differently depending on service and device. Third, I show how following a post on Facebook, our attention — to content and people — changes and shifts.

Speaker Biography: Mor Naaman is an associate professor of Information Science at the Jacobs Institute at Cornell Tech, where he is the founder of the Connective Media hub, and leads a research group focused on social technologies. His research applies multidisciplinary methods to 1) gain a better understanding of people and their use of social tech; 2) extract insights about people, technology and society from social media and other sources of social data, and 3) develop new social technologies as well as novel tools to make social data more accessible and usable in various settings. Previously, Mor was on the faculty at Rutgers SC&I, led a research team at Yahoo! Research Berkeley, received a Ph.D. in Computer Science from Stanford University, and played professional basketball for Hapoel Tel Aviv. He is a recipient of a NSF Early Faculty CAREER Award, research awards and grants from numerous corporations including AOL and Google, and multiple best paper awards. Find out more about Mor at http://mornaaman.com.

Time & Location: November 14, 2-6pm, Fairmount

2:00pm     Keynote 
                        Mor Naaman, Cornell Tech. Patterns of Large-Scale Attention in Social Media

2:45pm     Session 1: User Data Mining
                        Tianran Hu, Jiebo Luo, Henry Kautz, and Adam Sadilek, University of Rochester. Home Location Inference from Sparse and Noisy Data: Models and Applications
                        Longqi Yang, Cheng-Kang Hsieh, and Deborah Estrin, Cornell University. Beyond Classification: Latent User Interests Profiling from Visual Contents Analysis
                        Rupert Lemahieu, Steven Van Canneyt, Cedric De Boom, and Bart Dhoedt, Ghent University. Optimizing the Popularity of Twitter Messages through User Categories

3:45pm     Coffee Break

4:00pm     Session 2: Mining for Applications
                        Saurabh Kataria and Arvind Agarwal, PARC. Distributed Representations for Content-based and Personalized Tag Recommendation
                        Arpit Kumar Mishra, Ankit Malviya, and Sanchit Aggarwal, InnoPlexus. Towards Automatic Pharmacovigilance: Analysing Patient Reviews and Sentiment on Oncological Drugs
                        Nathan Fabian, Warren Davis, Elaine Raybourn, Kiran Lakkaraju, and Jon Whetzel, Grandmaster, Sandia National Labs. Interactive Text-based Analytics of Social Media

Organizers

Picture            Ching-Yung Lin photo             

Program Committee (tentative)

PC member access

Liangliang Cao, Yahoo Research

Saurabh Kataria, PARC

Yiannis Kompatsiaris, Information Technologies Institute (CERTH-ITI)

Tao Mei, Microsoft Research

Changsheng Xu, Chinese Academy of Science

Shenghuo Zhu, Alibaba Research

Haohong Wang, TCL Research America

Yi Yang, Baidu Big Data Lab

Webmaster

Quanzeng You, University of Rochester

FAQ

  • Q: What is the page limit?
    A: The workshop papers have the same page limit as the main conference. 
  • Q: I have a recent paper published elsewhere. Can I submit a short version to the workshop?
    A:  We encourage submissions of new work. Authors are also welcome to submit papers that have been recently published or accepted at another venue, as long as this information is disclosed at the time of submission.
  • Q: Will papers accepted to the workshop be published?
  • A: Workshops papers will be published in the CPS ICDMW 2015 Proceedings. 

Sponsors