research-article

Social linking and physical proximity in a mobile location-based service

Authors:

Li ZhangAuthors Info & Claims

MLBS '11: Proceedings of the 1st international workshop on Mobile location-based service

Pages 99 - 108

https://doi.org/10.1145/2025876.2025895

Published: 18 September 2011 Publication History

Abstract

In this paper we collected and examined the indoor location traces of users of an indoor location-based social network service called Find & Connect deployed at an academic conference, to explore the relation between users' physical proximity and the connecting properties of their social links. We define a parameter called encounter to represent the physical proximity between users, and also select two kinds of social links that exist in the online social graph formed during the conference, i.e., friendship and sharing common friends. Using these parameters, we present a correlation study of encounter duration, frequency and distribution with the formation and strength of the social links. Results show that, on average, an increasing encounter duration between users leads to a high possibility of the establishments of social links, while afterwards this increment of encounter duration slows down after establishments of social links. We also find users that are highly sociable (with regards to the number of friends and common friends) indicate a higher proximity interaction with their friends, and similarity of a pair of users suggests more and longer encounters between them. This means, for two kinds of social links we select, there is a strong relation between social linking and physical proximity.

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Cited By

Zhang HYu JLi MZhang YLing YZhang X(2022)Friend Relation Recognization Algorithm Based on The Campus Card ConsumptionProceedings of the 2022 11th International Conference on Computing and Pattern Recognition10.1145/3581807.3581883(515-521)Online publication date: 17-Nov-2022
https://dl.acm.org/doi/10.1145/3581807.3581883
Rahimi MMalek MClaramunt CLe Pors T(2021)A topology-based graph data model for indoor spatial-social networkingInternational Journal of Geographical Information Science10.1080/13658816.2021.191234935:12(2517-2539)Online publication date: 14-Apr-2021
https://doi.org/10.1080/13658816.2021.1912349
Carrasco-Jiménez JBrena RIglesias S(2020)Prediction of Social Ties Based on Bluetooth Proximity Time Series DataAdvances in Computational Intelligence10.1007/978-3-030-60887-3_37(435-446)Online publication date: 12-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-60887-3_37
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Index Terms

Social linking and physical proximity in a mobile location-based service
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Computer supported cooperative work
  2. Human computer interaction (HCI)
    1. HCI design and evaluation methods
2. Social and professional topics
  1. Professional topics
    1. Computing and business
      1. Computer supported cooperative work

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Published In

cover image ACM Conferences

MLBS '11: Proceedings of the 1st international workshop on Mobile location-based service

September 2011

118 pages

ISBN:9781450309288

DOI:10.1145/2025876

Program Chairs:
S.-H. Gary Chan
The Hong Kong University of Science and Technology, Hong Kong, P.R. China
,
Edward Y. Chang
Google Research, Beijing, P.R. China
,
Michael Lyu
The Chinese University of Hong Kong, Hong Kong, P.R. China

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Florida: University of Florida
SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 September 2011

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Ubicomp '11: The 2011 ACM Conference on Ubiquitous Computing

September 18, 2011

Beijing, China

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Cited By

Zhang HYu JLi MZhang YLing YZhang X(2022)Friend Relation Recognization Algorithm Based on The Campus Card ConsumptionProceedings of the 2022 11th International Conference on Computing and Pattern Recognition10.1145/3581807.3581883(515-521)Online publication date: 17-Nov-2022
https://dl.acm.org/doi/10.1145/3581807.3581883
Rahimi MMalek MClaramunt CLe Pors T(2021)A topology-based graph data model for indoor spatial-social networkingInternational Journal of Geographical Information Science10.1080/13658816.2021.191234935:12(2517-2539)Online publication date: 14-Apr-2021
https://doi.org/10.1080/13658816.2021.1912349
Carrasco-Jiménez JBrena RIglesias S(2020)Prediction of Social Ties Based on Bluetooth Proximity Time Series DataAdvances in Computational Intelligence10.1007/978-3-030-60887-3_37(435-446)Online publication date: 12-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-60887-3_37
Koch JSiering M(2019)The recipe of successful crowdfunding campaignsElectronic Markets10.1007/s12525-019-00357-829:4(661-679)Online publication date: 10-Aug-2019
https://doi.org/10.1007/s12525-019-00357-8
狄方(2018)Research on the Method of Finding out Unsociable StudentsComputer Science and Application10.12677/CSA.2018.8507208:05(637-648)Online publication date: 2018
https://doi.org/10.12677/CSA.2018.85072
Jang HChoe SGunkel SKang SSong J(2017)A System to Analyze Group Socializing Behaviors in Social PartiesIEEE Transactions on Human-Machine Systems10.1109/THMS.2016.263491847:6(801-813)Online publication date: Dec-2017
https://doi.org/10.1109/THMS.2016.2634918
Duarte LCarriço L(2016)Designing for geo-referenced in-situ therapeutic scenariosInformation Systems Frontiers10.1007/s10796-015-9576-z18:1(103-123)Online publication date: 1-Feb-2016
https://dl.acm.org/doi/10.1007/s10796-015-9576-z
Chin AXu BZhao CWang XDo ELi W(2014)From offline to onlineProceedings of the Second International Symposium of Chinese CHI10.1145/2592235.2592242(40-49)Online publication date: 26-Apr-2014
https://dl.acm.org/doi/10.1145/2592235.2592242
Yang DHung HLee WChen WGrossman RUthurusamy RDhillon IKoren Y(2013)Maximizing acceptance probability for active friending in online social networksProceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/2487575.2487599(713-721)Online publication date: 11-Aug-2013
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Xu BChin ACosley DMackay WBrewster SBødker S(2013)On how event size and interactivity affect social networksCHI '13 Extended Abstracts on Human Factors in Computing Systems10.1145/2468356.2468511(865-870)Online publication date: 27-Apr-2013
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