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LENS'18: Proceedings of the 2nd ACM SIGSPATIAL Workshop on Analytics for Local Events and News
ACM2018 Proceeding
  • Editors:
  • Amr Magdy,
  • Xun Zhou,
  • Liang Zhao,
  • Yan Huang
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Seattle WA USA 6 November 2018
ISBN:
978-1-4503-6035-7
Published:
06 November 2018
Sponsors:

Bibliometrics
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Abstract

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.

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research-article
Multiscale event detection using convolutional quadtrees and adaptive geogrids

Increasing popularity of social networks made them a viable data source for many data mining applications and event detection is no exception. Researchers aim not only to find events that happen in networks but more importantly to identify and locate ...

research-article
Analysis of Multifactorial Social Unrest Events with Spatio-Temporal k-Dimensional Tree-based DBSCAN

Clustering geospatial event data requires defining a distance function between events as well as representing neighborhood characteristics where an event occurred in numerical or categorical values. For events such as social unrest events, in addition ...

research-article
A Visual Analytics Framework for Big Spatiotemporal Data

Spatial visual analytics 1 is a critical aspect for big spatiotemporal data (BSTD) in exhibition the hidden spatiotemporal patterns. However, the real-time and dynamic characters of BSTD causes great challenges for the GIS domain and big data domain due ...

research-article
Public Access
Enhancing Local Live Tweet Stream to Detect News

Twitter captures invaluable information about real-world news, spanning a wide scale from large national/international stories like a presidential election to small local stories such as a local farmers market. Detecting and extracting small news for a ...

research-article
Public Access
Local Event Forecasting and Synthesis Using Unpaired Deep Graph Translations

Local rare event forecasting and synthesis on networks are highly useful for emergence management. For example, synthesizing traffic congestion and disease diffusion over the road network and disease-contact network respectively of specific geo-...

Contributors
  • University of California, Riverside
  • University of Iowa

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