Welcome to LENS 2018!

2nd ACM SIGSPATIAL International Workshop on Analytics for Local Events and News (LENS 2018)

November 6, 2018,
Seattle, Washington, USA



Aims and Scope

The advances in software and hardware technologies together with the rapid urbanization process globally over the last decade have changed the ways people interact as groups, both offline (physically), and online (virtually). On one hand, a growing urban population and diversity has led to more frequent social events of different types ranging from sports games and traffic congestion to ad-hoc gatherings and social protests. They may bring impacts on public safety, traffic, and business. On the other hand, online forums and social media have emerged as a new generator and information source for events and news. Using online services, e.g., social media and events-related websites, people have developed new ways of handling events such as continuously posted updates on events, organizing and broadcasting events via online means, and organizing events in virtual environments. Nevertheless, both online and offline events and news play important roles in modern societies. Consequently, identifying, forecasting, and understanding events and news has emerged as an important topic. By nature, events and news have spatial and temporal extents, suggesting that they are localized social phenomena. Spatiotemporal big data from social media, traffic sensors, vehicle trajectories, and location-based social network check-ins provide rich information that helps address the topic, while at the same time bring challenges such as large volume and high variety.

The workshop is intended to bring together experts from the research community and industry to exchange ideas on opportunities, challenges and cutting-edge techniques for local events and news analytics.

The workshop participants will be encouraged to submit full research papers and short position papers that discuss challenges and opportunities on topics that include, but not limited to, the following: