moved the International Workshop on
LBSN from ACM SIGSPATIAL GIS to UbiComp
The committee of the first three rounds of LBSN is now with the
UbiComp one. Another LBSN now with ACM SIGSPATIAL GIS has nothing to
do with the previous LBSNs. Please do not be confused.
The summary of LBSN 2012
The best paper award (Plaque)
"Local", "Categories" and "Friends": Clustering foursquare Users
with Latent "Topics"
Kenneth Joseph, Chun How Tan, Kathleen Carley
best student paper award
Crowd-sourced Cartography: Measuring Socio-cognitive Distance for
Urban Areas based on Crowd's Movement
Shoko Wakamiya, Ryong Lee, Kazutoshi SUMIYA
- LBSN 2012
will be held in Room 303,
David L. Lawrence
- Our workshop welcome
program of LBSN 2012 is online.
- You do not need the code for registration any
- Camera-ready instructions have been updated.
Our workshop code:
W01-LBSN. You need it for workshop registration.
- Accepted paper list is online.
- Camera-ready due is extended to July 16, 2012.
- Good News! A few high quality papers
will be invited to the
special issue on urban computing at ACM Trans. on Intelligent System and
- Paper submission site is open:
- Call for paper is being sent (Mar.
- Workshop homepage launched (Mar. 26, 2012).
Aims and Scope
Social networks have been prevalent on the
Internet and become a hot research topic attracting many
professionals from a variety of fields. The advances in
location-acquisition and mobile communication technologies empower
people to use location data with existing online social networks.
The dimension of location helps bridge the gap between the physical
world and online social networking services. Furthermore, people in
an existing social network can expand their social structure with
the new interdependency derived from their locations. As location is
one of the most important components of user context, extensive
knowledge about an individual’s interests, behaviors, and
relationships with others can be learned from her locations. These
kinds of location-embedded and location-driven social structures are
known as location-based social networks, formally defined as
location-based social network (LBSN) does not only mean adding a
location to an existing social network so that people in the social
structure can share location-embedded information, but also consists
of the new social structure made up of individuals connected by the
interdependency derived from their locations in the physical world
as well as their location-tagged media content, such as photos,
video, and texts. Here, the physical location consists of the
instant location of an individual at a given timestamp and the
location history that an individual has accumulated in a certain
period. Further, the interdependency includes not only that two
persons co-occur in the same physical location or share similar
location histories but also the knowledge, e.g., common interests,
behavior, and activities, inferred from an individual’s location
(history) and location-tagged data. 
 Yu Zheng.
Location-based social networks: Users. Computing with Spatial
Trajectories, Yu Zheng and Xiaofang Zhou, Eds. Springer, 2011.
 Yu Zheng.
Tutorial on Location-Based Social Networks. WWW2012.
In a location-based social network, people can
not only track and share the location-related information of an
individual via either mobile devices or desktop computers, but also
leverage collaborative social knowledge learned from user-generated
and location-related content, such as GPS trajectories and
geo-tagged photos. Consequently, LBSNs enable many novel
applications that change the way we live, such as travel planning,
location recommendations, friend suggestion, and community
discovery, while offering many new research opportunities to the
Ubiquitous computing community, including link prediction, human
mobility modeling, and user activity recognition, privacy, and
computer human interaction.
Example papers and free datasets can be found on
The objective of this workshop
is to provide professionals, researchers, and technologists with a
single forum where they can discuss and share the state-of-the-art
of LBSN development and applications, present their ideas and
contributions, and set future directions in emerging innovative
research for location based social networks.
Topics of Interest
Topics of interest include, but not limited to, the following aspects :
Understanding users in LBSNs
User preference modeling
User mobility modeling and analysis
Real-world user activity sensing
User similarity computing based on
Link prediction and social tiers
Friend recommendations and
Expert discovery and influential
User intension understanding
Understanding locations in LBSNs
Hot spots, significant places, and
interesting locations detection
Generic or personalized location
Popular travel routes discovery
from social media
Trip planning and itinerary
suggestion for users
Location annotation and semantic
Location prediction and location
Anomaly detection and event
discovery from social media
Trajectory data mining in LBSNs
Information sharing and Data management in LBSNs
Location and location-related data
Location and location-tagged media
Human-computer interaction in LBSNs
Information retrieval in LBSNs.
Data management in LBSNs.