Classifying urban events' popularity by analyzing friends information in location-based social network

Makoto Kawano, Takuro Yonezawa, Jin Nakazawa, Satoshi Kawasaki, Ken Ohta, Hiroshi Inamura, Hideyuki Tokuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recent progress and spread of smartphones and social network services have enabled us to transmit text messages with GPS location data anywhere and anytime. Since these location-based SNS messages often refer to urban events, many researchers have tried to recognize urban events by analyzing of the messages. To construct the various applications based on the urban events information, we propose a new indicator of event, called Popularity which represents how popular the urban event is. Popularity is estimated by analyzing friends on social network of events' participants. To evaluate our new indicator, we designed and implemented intuitive and interactive web-based tool for analyzing Popularity of events. Through comparative experiments, we confirmed that our proposed method could provide a certain amount of accuracy for estimating Popularity of events.

Original languageEnglish
Title of host publicationUrb-IoT 2014 - 1st International Conference on IoT in Urban Space, Conference Proceedings
PublisherICST
Pages87-89
Number of pages3
ISBN (Electronic)9781631900372
DOIs
Publication statusPublished - 2014 Oct 27
Event1st International Conference on IoT in Urban Space, Urb-IoT 2014 - Rome, Italy
Duration: 2014 Oct 272014 Oct 28

Publication series

NameUrb-IoT 2014 - 1st International Conference on IoT in Urban Space, Conference Proceedings

Conference

Conference1st International Conference on IoT in Urban Space, Urb-IoT 2014
Country/TerritoryItaly
CityRome
Period14/10/2714/10/28

Keywords

  • Location-based social network
  • Urban event classification

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Software
  • Civil and Structural Engineering
  • Development
  • Geography, Planning and Development
  • Urban Studies

Fingerprint

Dive into the research topics of 'Classifying urban events' popularity by analyzing friends information in location-based social network'. Together they form a unique fingerprint.

Cite this