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Social Network Analysis using Mobile Phone Data
António Pedro OliveiraUniversity of Coimbra, Portugal
Introduction
Motivation Social networks
Social media (facebook, twitter, linkedin) Obtain, web crawling of data Find relations among people Understand relations’ type
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Introduction Research Areas Data Tools Conclusion
Research Areas Social Network Analysis
Software tools Gephi
Nodes Edges Adjacency matrix Node degree
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Introduction Research Areas Data Tools Conclusion
Research Areas Social Network Analysis
Centrality of a node in degree (number of incoming edges), out degree (number of outcoming edges), betweenness (number of pairs of nodes
that go through you) closeness (average distance of one node to
anothers)
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Introduction Research Areas Data Tools Conclusion
Research Areas Social Network Analysis
Community mutuality of ties (everybody in the group knows
everybody else) frequency of ties among members (everybody in
the group has links to at least k others in the group)
cliques (every member of the group has links to every other member)
clustering
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Introduction Research Areas Data Tools Conclusion
Research Areas
Social Network Analysis Finding motifs (small structures) in
network models Average shortest path
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Introduction Research Areas Data Tools Conclusion
Data
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Introduction Research Areas Data Tools Conclusion
Two main files cell_dim and call_fct cell_dim file presents longitude, latitude
and regions for each cell tower (1) cell_id (5) longitude (6) latitude (7) region = region ID (There are 3 regions)
Data
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Introduction Research Areas Data Tools Conclusion
call_fct file presents caller ID and callee ID and respective cell towers, as well as the date and duration of the call
(1) originating_id (caller ID) (2) originating_cell_id (caller's cell tower) (3) terminating_id (callee ID) (4) terminating_cell_id (callee's cell tower) (5) date_id (6) duration_amt (duration of the call)
Data
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Introduction Research Areas Data Tools Conclusion
lisbon_subject_id file has the subjects’ ids of Lisbon which helps us to identify phone calls of Lisbon
fct_call_oneDay is a file obtained with the phone calls for only one day
Using Mobile Phone Data
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Introduction Research Areas Data Tools Conclusion
Which opportunities we find on cellphone data of OPTIMUS
Grouping people Location of people People mobility (means of transport, POIs) Duration of phone calls Date
Tools
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Introduction Research Areas Data Tools Conclusion
Gephi Clustering algorithm (MCL)
Divide the social network in clusters of points Some of the various statistics parameters
Average degree Network diameter Graph density Average clustering coefficient Average path length
Tools
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Introduction Research Areas Data Tools Conclusion
Gephi (fct_max_300(id))
Using Mobile Phone Data
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Introduction Research Areas Data Tools Conclusion
Select data of one day, where the caller is in a specific location (for instance, in Lisbon) Obtain a social network For the ones with the longer duration’s
calls represent the location in QGIS
Tools
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Introduction Research Areas Data Tools Conclusion
Gephi (fct_lisbon_oneDay)
Tools
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Introduction Research Areas Data Tools Conclusion
Postgres To select cell towers from LisbonSELECT id, latitude, longitude
FROM cell_dim
WHERE latitude < -9.10 AND latitude > -9.42
AND longitude > 38.69 AND longitude < 38.96
LIMIT 10000
Tools
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Introduction Research Areas Data Tools Conclusion
Postgres To select phone calls of one day with cell
towers belonging to Lisbonselect *
from fct_call
where date_id >= 35100000 AND date_id < 35200000
AND (originating_cell_id = 10011 OR …)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (longer phone calls in Lisbon)
Tools
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Introduction Research Areas Data Tools Conclusion
Use previous data and for each hour in a day identify subjects with the higher duration of calls Present the variation for each hour in
QGIS
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 0)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 1)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 2)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 3)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 4)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 5)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 6)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 7)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 8)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 9)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 10)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 11)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 12)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 13)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 14)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 15)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 16)
Tools
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Introduction Research Areas Data Tools Conclusion
QGIS (hour 17)
Conclusions Challenges
Obtain semantic information from mobile phone data
Understand the meaning of the (groups in) social networks (friendship?)
Understand geographic information Relate social networks with geographic information The mobility of the users (POIs?) Obtain profile for the users
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Introduction Research Areas Data Tools Conclusion
Conclusions
We are using mobile phone data of OPTIMUS to find social networks
We obtained social networks with small groups (of interactions)
We showed the distribution of mobile phone data on a GIS
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Introduction Research Areas Data Tools Conclusion
The End
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