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ThinkMind // PATTERNS 2017, The Ninth International Conferences on Pervasive Patterns and Applications // View article patterns_2017_6_20_78009


Analysing Human Migrations Patterns Using Digital Social Network Analysis

Authors:
Charles Perez

Keywords: Social media, Social network analysis, Region of Interests, Migration,Spatio-temporal graphs, Twitter

Abstract:
The success of smartphones and digital social networks has permitted a constant increase in the mobile social networks of users in the last decades. It is now possible for anyone to share content with enriched metadata, providing user’s context and, in particular, times and locations. Contextual information associated with messages’ content allows for the large-scale analysis of users’ spatio-temporal behaviour, affording various possible applications (e.g., geo-marketing, security, smart cities). A number of studies have focused on spatio-temporal social data analyses for event detection and the identification of region of interests. This paper proposes a methodology that relies on social network analyses to identify the migrations of users between regions of interest. The proposed methodology allows for the capture of similar events and their characterization by participants’ behaviour (source location and destination, etc.). The methodology is tested on 3 millions tweets from the San Francisco Bay Area.

Pages: 82 to 87

Copyright: Copyright (c) IARIA, 2017

Publication date: February 19, 2017

Published in: conference

ISSN: 2308-3557

ISBN: 978-1-61208-534-0

Location: Athens, Greece

Dates: from February 19, 2017 to February 23, 2017

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