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LENS'19: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Local Events and News
ACM2019 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Chicago IL USA 5 November 2019
ISBN:
978-1-4503-6958-9
Published:
05 November 2019
Sponsors:
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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. Spatio-temporal 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
A Blockchain-based Solution to Fake Check-ins in Location-Based Social Networks
Article No.: 1, Pages 1–4https://doi.org/10.1145/3356473.3365191

Location-Based Social Networks (LBSNs) are an emerging kind of social network in which users can share their position with others and talk about visited places, providing comments and recommendations. Some LBSNs encourage the voluntary submission of ...

research-article
Open Access
Scalable Community Detection over Geo-Social Network
Article No.: 2, Pages 1–10https://doi.org/10.1145/3356473.3365189

We consider a community finding problem called Co-located Community Detection (CCD) over geo-social networks, which retrieves communities that satisfy both high structural tightness and spatial closeness constraints. To provide a solution that benefits ...

research-article
DeepSpot: Understanding Online Opinion Spam by Text Augmentation using Sentiment Encoder-Decoder Networks
Article No.: 3, Pages 1–10https://doi.org/10.1145/3356473.3365187

Recently opinion spam has been widespread on online review websites and has received significant research attention. Existing approaches to detecting online opinion spam can be categorized into three groups: (1) review behavior-based approaches, which ...

research-article
Public Access
DeLLe: Detecting Latest Local Events from Geotagged Tweets
Article No.: 4, Pages 1–10https://doi.org/10.1145/3356473.3365188

Geotagged tweet streams contain invaluable information about the real-world local events like sports games, protests and traffic accidents. Timely detecting and extracting such events may have various applications but yet unsolved challenges. In this ...

research-article
Public Access
Detecting (Unusual) Events in Urban Areas using Bike-Sharing Data
Article No.: 5, Pages 1–7https://doi.org/10.1145/3356473.3365190

Social media, traffic sensors, GPS trajectories, and location-based social network data provide diverse Spatio temporal information sources that help to detect and analysis Spatio temporal events. Nowadays, bike sharing systems are active all over the ...

Contributors
  • University of Maryland, College Park
  • University of California, Riverside

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