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Proximates - A Social Context Engine

Jonsson, Håkan LU and Nugues, Pierre LU (2013) 413. p.230-239
Abstract
Several studies have shown the value of using proximity data to understand the social context of users. To simplify the use of social context in application development we have developed Proximates, a social context engine for mobile phones. It scans nearby Bluetooth peers to determine what devices are in proximity. We map Bluetooth MAC ids to user identities on existing social networks which then allows Proximates to infer the social context of the user. The main contribution of Proximates is its use of link attributes retrieved from Facebook for granular relationship classification. We also show that Proximates can bridge the gap between physical and digital social interactions, by showing that it can be used to measure how much time a... (More)
Several studies have shown the value of using proximity data to understand the social context of users. To simplify the use of social context in application development we have developed Proximates, a social context engine for mobile phones. It scans nearby Bluetooth peers to determine what devices are in proximity. We map Bluetooth MAC ids to user identities on existing social networks which then allows Proximates to infer the social context of the user. The main contribution of Proximates is its use of link attributes retrieved from Facebook for granular relationship classification. We also show that Proximates can bridge the gap between physical and digital social interactions, by showing that it can be used to measure how much time a user spends in physical proximity with his Facebook friends. In this paper we present the architecture and initial experimental results on deployment usability aspects of users of an example application. We also discuss using location for proximity detection versus direct sensing using Bluetooth. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Evolving Ambient Intelligence/Communications in Computer and Information Science
volume
413
pages
230 - 239
publisher
Springer
external identifiers
  • scopus:84904758897
ISSN
1865-0929
ISBN
978-3-319-04405-7
DOI
10.1007/978-3-319-04406-4_23
project
Embedded Applications Software Engineering
language
English
LU publication?
yes
id
dabd6e5b-e86a-4cbe-a126-881166b2db81 (old id 4249429)
date added to LUP
2016-04-01 13:11:32
date last changed
2019-03-19 01:57:02
@inproceedings{dabd6e5b-e86a-4cbe-a126-881166b2db81,
  abstract     = {Several studies have shown the value of using proximity data to understand the social context of users. To simplify the use of social context in application development we have developed Proximates, a social context engine for mobile phones. It scans nearby Bluetooth peers to determine what devices are in proximity. We map Bluetooth MAC ids to user identities on existing social networks which then allows Proximates to infer the social context of the user. The main contribution of Proximates is its use of link attributes retrieved from Facebook for granular relationship classification. We also show that Proximates can bridge the gap between physical and digital social interactions, by showing that it can be used to measure how much time a user spends in physical proximity with his Facebook friends. In this paper we present the architecture and initial experimental results on deployment usability aspects of users of an example application. We also discuss using location for proximity detection versus direct sensing using Bluetooth.},
  author       = {Jonsson, Håkan and Nugues, Pierre},
  booktitle    = {Evolving Ambient Intelligence/Communications in Computer and Information Science},
  isbn         = {978-3-319-04405-7},
  issn         = {1865-0929},
  language     = {eng},
  pages        = {230--239},
  publisher    = {Springer},
  title        = {Proximates - A Social Context Engine},
  url          = {http://dx.doi.org/10.1007/978-3-319-04406-4_23},
  doi          = {10.1007/978-3-319-04406-4_23},
  volume       = {413},
  year         = {2013},
}