COOL-SNA 2014 - The 1st COOL-SNA Workshop on Connecting Online and Offline Social Network Analysis

The 1st COOL-SNA workshop is proposed as the first workshop on "Connecting Online and Off-Line Social Network Analysis" to be co-held with ICDM, soliciting experimental and theoretical work on social network mining and analysis with a particular interest in those studies that examine the connection between online and offline social network systems.
Social network research has achieved significant advances thanks to the prevalence of all kinds of online social network services. A wealth of research results have been obtained by the community along the years on various aspects of users' online social behavior, e.g., social influence. Yet there has been little study on how the results in online social network would translate into the corresponding impact in our offline real life. For example, how many offline real purchasing transactions will actually result from the influence of a so-called "highly influential" user in the online social platform? How do one's online social connections relate to his/her offline real-world friendship circle? Answers to such questions are profoundly important to connect all the analysis results on online social data to real-life application settings in the physical world, where still most of the business transactions and social interactions take place.
A user's online and offline social network inform and complement each other. The juxtaposition of the various information diffusion, user interaction, item adoption as well as network evolution in online platforms and offline real world offers an interesting perspective to examine the interplay between the two worlds.
Accordingly, both academia and industry are increasingly interested in addressing a wide range of challenges residing in the overlapped realm of these disparate online and offline social network systems, including identifying common static topological properties and dynamic properties during the formation and evolution of the social networks, exploring how contextual information can help analyze the pertaining social networks and how offline behaviors are connected to their online social circles.
The 1st COOL-SNA workshop will focus on knowledge discovery and data mining in connecting online and offline social networks, such as user profiling, behavior analysis, event detection, decision modeling, contextual community discovery, link analysis, the growth and evolution of social networks, algorithms for large scale graphs, techniques that can be used for recovering and constructing social networks from connection online and offline social systems, search on social networks, multi-agent based social network simulation, trend prediction of social network evolution, and related applications in other domain such as information retrieval and recommendation systems. The workshop is concerned with inter-disciplinary and cross-domain studies that would lead to deeper understanding of the two worlds.
Keynote Speech: We plan to invite two keynote speakers, one from academia and one from industry, to give pubic talks/panel in the workshop. These talks will stress the interdisciplinary challenges of the social network analysis and mining.
Proceedings: Papers accepted for presentation at the workshop will be published in the workshop proceedings of the ICDM conference by the IEEE Computer Society Press.
Student travel award: We will award one Best Paper Award, and sponsor several travel grants for students in need. The sponsorship has already been secured.
Workshop Topics Top
Topics of Interest:
The 1st COOL-SNA 2014 aims to bring together practitioners and researchers with a specific focus on the emerging trends and industry needs associated with online social network, offline social behavior analysis, and their connection. Both theoretical and experimental submissions are encouraged. The interesting topics include (1) data mining advances on the discovery and analysis of online and offline (OO) connected communities, on OO personalization for solitary activities (like search) and OO social activities (like discovery of potential friends), on the analysis of user behavior in open fora (like conventional sites, blogs and fora) and in commercial platforms (like e-auctions) and on the associated security and privacy-preservation challenges; (2) OO social network modeling, scalable, customizable social network infrastructure construction, dynamic growth and evolution patterns identification and discovery using machine learning approaches or multi-agent based simulation.
Papers should elaborate on data mining methods, issues associated to data preparation and pattern interpretation, both for conventional data (usage logs, query logs, document collections) and for multimedia data (pictures and their annotations, multi-channel usage data). Topics of interest include but are not limited to:
Online and offline social network connection analysis;
Online and offline social behavior connection analysis;
Online and offline social event detection and prediction;
Online and offline recommendation;
Spatial, temporal and social decision analysis;
Communities discovery and analysis in large scale online and offline social networks;
Personalization for online and offline search social interaction;
Online and offline recommendations for product purchase, information acquisition and establishment of social relations;
Data protection inside communities;
Misbehavior detection in communities;
Web mining algorithms for clickstreams, documents and search streams;
Pattern presentation for end-users and experts;
Evolution of patterns in the online and offline social network;
Evolution of communities in the online and offline social network;
Dynamics and evolution patterns of online and offline social networks, trend prediction;
Contextual online and offline social network analysis;
Temporal analysis on online and offline social networks topologies;
Search algorithms on online and offline social networks;
Multi-agent based online and offline social network modeling and analysis;
Application of online and offline social network analysis;
Anomaly detection in online and offline social network evolution;
Role identification and relation analysis in social network;
Collective social network integration and analysis.