-------- Original-Nachricht -------- Betreff: [WI] CfP: 5th International Workshop on Modeling Social Media @ WWW 2014 Datum: Tue, 19 Nov 2013 15:05:39 +0000 Von: Martin Atzmueller atzmueller@cs.uni-kassel.de An: kdml@cs.uni-kassel.de, ak-kd-list@lists.uni-karlsruhe.de, wi@aifb.uni-karlsruhe.de, fg-db@informatik.uni-rostock.de
CALL FOR PAPERS -------------------------------------------------------------- 5th International Workshop on Modeling Social Media (MSM'2014)
Mining Big Data in Social Media and the Web http://www.kde.cs.uni-kassel.de/ws/msm2014/ to be held on April 8, 2014, Seoul, Korea
co-located with ACM WWW 2014 --------------------------------------------------------------
Important Dates: ** Submission Deadline: January 7, 2014 (23:59 Hawaii Standard Time) ** Notification of Acceptance: Feb 4, 2014
** Final Papers Due: Feb 12, 2014
** Workshop date: April 8, 2014
Workshop Organizers: Alvin Chin, Nokia, Beijing, China; alvin.chin@nokia.com Martin Atzmueller, University of Kassel, Kassel, Germany; atzmueller@cs.uni-kassel.de Christoph Trattner, Know-Center, Graz University of Technology, Graz, Austria; trattner.christoph@gmail.com
In our first workshop on Modeling Social Media (MSM 2010 in Toronto, Canada), we explored various different models of social media ranging from user modeling, hypertext models, software engineering models, sociological models and framework models. In our second workshop (MSM 2011 in Boston, USA), we addressed the user interface aspects of modeling social media. In our third workshop (MSM 2012 in Milwaukee, USA), we looked at the collective intelligence in social media, i.e. making sense of the content and context from social media websites such as Facebook, Twitter, Google+ and Foursquare by analyzing tweets, tags, blog posts, likes, posts and check-ins, in order to create a new knowledge and semantic meaning. Last year's workshop (MSM 2013 in Paris, France), we discussed about mining, modeling and recommending "things" in social media.
For this workshop, we aim to attract researchers from all over the world working in the field of big data mining and machine learning using web and social media data. Big data is a hot topic in the research community, and we would like to invite researchers in the data and web mining community to lend their expertise to help make understanding of the web and social media that we have out there (e.g. Facebook and Twitter, and browsing web logs). Thus, we invite submissions which may include the following topics, but are not limited to:
* novel big data mining and analytics methods or frameworks for social media and the web * novel approaches for personalization and recommendations * novel methods for social structure and community discovery * novel methods for tie strength or link prediction * novel methods for predicting user behavior * novel methods for user modeling and profiling * novel methods for big data information visualization * privacy and security issues in mining big data from web and social media * applications of any of the above methods and technologies
The goal of this workshop is to apply big data mining approaches and algorithms on social media. Big data is everywhere and social media is now becoming one of the proponents of generating big data, especially since the data is in real time. Every company internally and externally has big data, but the issue is how to mine and make use of this big data to help companies make informed decisions. This workshop helps to address methods, algorithms, and frameworks to solve this problem from expert researchers. Hence, the workshop aims to attract and discuss various novel aspects of personalization, recommendation, community discovery, profiling and prediction from social media. In short the workshop invites topics that deal with user and social behavior that is inferred from mining the social media through big data analytics. Thus, our goal is to bring together researchers and practitioners from around the world in the big data mining, machine learning and recommendation communities interested in
1) exploring different perspectives and approaches to mine (complex) and analyze social media data, 2) inferring user and social behavior through big data analytics, personalization and recommendation and 3) building models and frameworks for evaluating the designed approaches.
Submissions: We solicit short position papers (1-2 pages) and peer-reviewed research papers (4-8 pages) in the ACM conference paper style. Papers should be submitted in EasyChair to https://www.easychair.org/conferences/?conf=msm2014
Program Committee: * Alejandro Bellogin, Universidad Autonoma de Madrid, Spain * Shlomo Berkovsky, NICTA, Australia * Robin Burke, de Paul, USA * Javier Luis Canovas, Izquierdo, INRIA, France * Polo Chau, Georgia Tech, USA * Guanling Chen, University of Massachussetts – Lowell, USA * Padraig Cunningham, University College Dublin, Ireland * Daniel Gayo-Avello, University of Oviedo, Spain * Michael Granitzer, University of Passau, Germany * Ido Guy, IBM Research, Israel * Eelco Herder, L3S, Germany * Andreas Hotho, University of Wuerzburg, Germany * Geert-Jan Houben, TU-Delft, Netherlands * Elisabeth Lex, Know-Center, Austria * Kris Jack, Mendeley, UK * Else Nygren, Uppsala University, Sweden * Ralf Klamma, RWTH Aachen, Germany * Thomas Kannampallil, University of Texas, USA * Denis Parra, PUC, Chile * Haggai Roitman, IBM Research, Israel * James She, Hong Kong University of Science and Technology, Hong Kong * Christoph Scholz, University of Kassel, Germany * Marc Smith, ConnectedAction, USA * Zhiyong Yu, Institut Telecom Sud de Paris, France * Shengdong Zhao, National University of Singapore, Singapore * Arkaitz Zubiaga, New York City University, USA
Proceedings: We intend to include the publications in the ACM WWW Conference Proceedings and provide them to the attendees of the conference on a USB stick.
Contact: msm2014pc@gmail.com
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