Social networks and social media are prevalent on the Internet and have become an active research topic attracting many professionals and researchers from a variety of fields. By adding trajectory information, we can bring online social networks and media back to the physical world and share our real-life experiences in the virtual world conveniently. By mining trajectory patterns or predicting locations from social networks, people can not only track and share location-related information with each other via mobile devices or desktop computers, but can also leverage collaborative social knowledge learned from user-generated and location-related content. As trajectory is one of the most important properties in people's everyday lives, the research on trajectory mining in social networks (TMSN) bridges the gap between online societies and the physical world, and enable novel applications that have the potential to change the way we live, e.g., path planning/prediction, friend suggestion, location/friend recommendations, community discovery, human mobility modeling, and user activity analysis. The technology derived from TMSN, e.g., trajectory mining and retrieval, can be applied to a multitude of other research areas including biology, sociology, geography, and climatology as well.

This TMSN 2013 workshop intends to bring together researchers and practitioners from academia and industry to discuss and share the state-of-the-art in TMSN development and application, present their ideas and contributions, and set the future direction of TMSN research. In this workshop, we would like to broaden the focus to include location based social media more generally.

The workshop welcomes various different kinds of papers that could handle the novel, difficult and challenging problems in existing location based social networks research domain. Papers of applied research, industrial experience reports, work-in-progress and vision papers with different criteria for each category are also solicited. The best presented paper will receive the BEST PAPER AWARD.

TOPICS:
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The topics of interest include, but are not limited to the following:

Spatial and spatio-temporal data mining in user-centric scenarios
Moving object tracking, indexing and retrieval for social applications
Trajectory compressing and simplification
Trajectory data mining, pattern recognition, and knowledge discovery
Location privacy and security
Uncertainty of trajectory in modeling, inference, and querying
Activity recognition and sensing for social applications
Location identification from sensor data for social applications
User behavior modeling using physical sensor data
Semantic meaning and knowledge discovery from trajectory data
User similarity computing based on location-related information
Social structure detection from location-related data
Location and friend recommendations
Hot spots, significant places, and interesting trajectory pattern detection
Location-tagged media sharing and mining
Human-computer interaction in location-based social networks
Mobile and ubiquitous computing for location-based social networks
Information retrieval in location-based social networks
Location and location-related data sharing
Location and location-tagged media visualization
Human-computer interaction in TMSN.
Information retrieval in TMSN.
Data management in TMSN.