Merging Inhomogeneous Proximity Sensor Systems for Social Network Analysis

Amir Muaremi; Franz Gravenhorst; Julia Seiter; Agon Bexheti; Bert Arnrich; Gerhard Tröster

Mobile and Ubiquitous Systems: Computing, Networking, and Services. 10th International Conference, MOBIQUITOUS 2013, Tokyo, Japan, December 2-4, 2013, Revised Selected Papers

Research Article

Merging Inhomogeneous Proximity Sensor Systems for Social Network Analysis

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@INPROCEEDINGS{10.1007/978-3-319-11569-6_15,
    author={Amir Muaremi and Franz Gravenhorst and Julia Seiter and Agon Bexheti and Bert Arnrich and Gerhard Tr\o{}ster},
    title={Merging Inhomogeneous Proximity Sensor Systems for Social Network Analysis},
    proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 10th International Conference, MOBIQUITOUS 2013, Tokyo, Japan, December 2-4, 2013,  Revised Selected Papers},
    proceedings_a={MOBIQUITOUS},
    year={2014},
    month={12},
    keywords={Proximity Smartphones Bluetooth ANT
               Pilgrims},
    doi={10.1007/978-3-319-11569-6_15}
}

Amir Muaremi
Franz Gravenhorst
Julia Seiter
Agon Bexheti
Bert Arnrich
Gerhard Tröster
Year: 2014
Merging Inhomogeneous Proximity Sensor Systems for Social Network Analysis
MOBIQUITOUS
Springer
DOI: 10.1007/978-3-319-11569-6_15

Amir Muaremi¹^,*, Franz Gravenhorst¹^,*, Julia Seiter¹^,*, Agon Bexheti²^,*, Bert Arnrich³^,*, Gerhard Tröster¹^,*

1: ETH Zurich
2: EPFL
3: Bogaziçi University

*Contact email: muaremi@ife.ee.ethz.ch, gravenhorst@ife.ee.ethz.ch, seiter@ife.ee.ethz.ch, agon.bexheti@epfl.ch, bert.arnrich@boun.edu.tr, troester@ife.ee.ethz.ch

Abstract

Proximity information is a valuable source for social network analysis. Smartphone based sensors, like GPS, Bluetooth and ANT, can be used to obtain proximity information between individuals within a group. However, in real-life scenarios, different people use different devices, featuring different sensor modalities. To draw the most complete picture of the spatial proximities between individuals, it is advantageous to merge data from an inhomogeneous system into one common representation. In this work we describe strategies how to merge data from Bluetooth sensors with data from ANT sensors. Interconnection between both systems is achieved using pre-knowledge about social rules and additional infrastructure. Proposed methods are applied to a data collection from 41 participants during an 8 day pilgrimage. Data from peer-to-peer sensors as well as GPS sensors is collected. The merging steps are evaluated by calculating state-of-the art features from social network analysis. Results indicate that the merging steps improve the completeness of the obtained network information while not altering the morphology of the network.

Keywords: Proximity Smartphones Bluetooth ANT Pilgrims

Published: 2014-12-10

: http://dx.doi.org/10.1007/978-3-319-11569-6_15