Paper Info
Title
A Crowd Sensing System Identifying Geotopics And Community Interests From User-Generated Content
Abstract
This paper presents a crowd sensing system (CSS) that captures geospatial social media topics and allows the review of results. Using Web-resources derived from social media platforms, the CSS uses a spatially-situated social network graph to harvest user-generated content from selected organizations and members of the public. This allows passively' contributed social media-based opinions, along with different variables, such as time, location, social interaction, service usage, and human activities to be examined and used to identify trending views and influential citizens. The data model and CSS are used for demonstration purposes to identify geotopics and community interests relevant to municipal affairs in the City of Toronto, Canada.
Year
DOI
Venue
2019
10.1080/13658816.2019.1591413
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
Keywords
Field
DocType
Social media, smart city, big data, public participation, public opinion, data models
Social relation,Geospatial analysis,User-generated content,Data science,Social media,Public participation,Computer science,Public opinion,Artificial intelligence,Smart city,Big data,Machine learning
Journal
Volume
Issue
ISSN
33
8
1365-8816
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
M. Tenney100.34
B. Hall213321.11
R. E. SIEBER3185.62