Authors:
Maarten Wijnants
;
Adam Blazejczak
;
Peter Quax
and
Wim Lamotte
Affiliation:
Hasselt University, Belgium
Keyword(s):
Twitter, Social Networking Sites (SNSs), Social Media, TweetPos, Geographic Trends, Investigative Tool.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Internet Technology
;
Sensor Networks
;
Signal Processing
;
Social Media Analytics
;
Social Networks and Organizational Culture
;
Society, e-Business and e-Government
;
Soft Computing
;
Web Geographical Information Systems
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
;
Web Services and Web Engineering
Abstract:
Popular Social Networking Sites (SNSs) like Twitter and Facebook are evolving into crowd-sourced, interdisciplinary
sensor systems that “monitor” a wide spectrum of (physical) properties and topics. This paper
introduces TweetPos, a web service that is intended to facilitate the analytical study of geographic tendencies
in Twitter data feeds. To oblige the human cognitive features, the TweetPos tool maximally relies on visual
data structures like heatmaps and charts to represent the geo-spatial sources of tweets. The tool compiles data
bodies that grant insight in both past and present tweet posting behavior, incorporates an animation engine
to highlight temporal trends, and leverages layered visualization techniques so that multiple topics can be
offset against each other, all from a geographic perspective. Via the presentation of two representative use
cases, we comprehensively demonstrate TweetPos’ data mining and analytical features and we illustrate the
(geo-spatial) intelligenc
e they can amount to. Thanks to a generic implementation, the TweetPos service is
not geared towards a specific target audience but instead is sufficiently versatile to be valuable for a vast and
varied collection of consumer profiles like social scientists and market analysts.
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