research-article

Find me if you can: improving geographical prediction with social and spatial proximity

Authors:

Lars Backstrom,

Cameron MarlowAuthors Info & Claims

WWW '10: Proceedings of the 19th international conference on World wide web

Pages 61 - 70

https://doi.org/10.1145/1772690.1772698

Published: 26 April 2010 Publication History

Abstract

Geography and social relationships are inextricably intertwined; the people we interact with on a daily basis almost always live near us. As people spend more time online, data regarding these two dimensions -- geography and social relationships -- are becoming increasingly precise, allowing us to build reliable models to describe their interaction. These models have important implications in the design of location-based services, security intrusion detection, and social media supporting local communities.

Using user-supplied address data and the network of associations between members of the Facebook social network, we can directly observe and measure the relationship between geography and friendship. Using these measurements, we introduce an algorithm that predicts the location of an individual from a sparse set of located users with performance that exceeds IP-based geolocation. This algorithm is efficient and scalable, and could be run on a network containing hundreds of millions of users.

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https://doi.org/10.3390/info16010065
Paul AChangder NDutta A(2025)DSF-GAM: a location inference model in social network TwitterInternational Journal of Computers and Applications10.1080/1206212X.2024.244849747:2(141-161)Online publication date: 9-Jan-2025
https://doi.org/10.1080/1206212X.2024.2448497
Roskruge MPoot J(2024)The Relationship between Social Capital and Migrant Integration, Ethnic Diversity, and Spatial SortingSSRN Electronic Journal10.2139/ssrn.4831652Online publication date: 2024
https://doi.org/10.2139/ssrn.4831652
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Information

Published In

cover image ACM Other conferences

WWW '10: Proceedings of the 19th international conference on World wide web

April 2010

1407 pages

ISBN:9781605587998

DOI:10.1145/1772690

General Chairs:
Michael Rappa
North Carolina State University, USA
,
Paul Jones
University of North Carolina at Chapel Hill, USA
,
Program Chairs:
Juliana Freire
University of Utah, USA
,
Soumen Chakrabarti
Indian Institute of Technology, India

Copyright © 2010 International World Wide Web Conference Committee (IW3C2).

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2010

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WWW '10

WWW '10: The 19th International World Wide Web Conference

April 26 - 30, 2010

North Carolina, Raleigh, USA

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Elteir M(2025)Fine-Grained Arabic Post (Tweet) Geolocation Prediction Using Deep Learning TechniquesInformation10.3390/info1601006516:1(65)Online publication date: 18-Jan-2025
https://doi.org/10.3390/info16010065
Paul AChangder NDutta A(2025)DSF-GAM: a location inference model in social network TwitterInternational Journal of Computers and Applications10.1080/1206212X.2024.244849747:2(141-161)Online publication date: 9-Jan-2025
https://doi.org/10.1080/1206212X.2024.2448497
Roskruge MPoot J(2024)The Relationship between Social Capital and Migrant Integration, Ethnic Diversity, and Spatial SortingSSRN Electronic Journal10.2139/ssrn.4831652Online publication date: 2024
https://doi.org/10.2139/ssrn.4831652
Fawzi MMagdy W(2024)"Pinocchio had a Nose, You have a Network!": On Characterizing Fake News Spreaders on Arabic Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/36537028:CSCW1(1-20)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3653702
Fei GLiu YHu GWen SXiang Y(2024)Online Social Network User Home Location Inference Based on Heterogeneous NetworksIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2024.337637221:6(5509-5525)Online publication date: Nov-2024
https://doi.org/10.1109/TDSC.2024.3376372
Mukhamedova FTyukin I(2024)Machine learning analysis of the effects of COVID-19 on migration patternsScientific Reports10.1038/s41598-024-80841-014:1Online publication date: 30-Nov-2024
https://doi.org/10.1038/s41598-024-80841-0
Tarafdar MMinaei-Bidgoli B(2024)A Co-occurrence Prediction Framework in Location-Based Social NetworksNew Generation Computing10.1007/s00354-024-00276-z42:5(1129-1163)Online publication date: 20-Sep-2024
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Zhang GZhao PZhang AZhang GZhao PZhang A(2024)LocMIA: Membership Inference Attacks Against Aggregated Location DataPrivacy Preservation in Distributed Systems10.1007/978-3-031-58013-0_1(3-24)Online publication date: 8-Apr-2024
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Al-Jamaan RYklef MAlothaim A(2023)GLDM: Geo-location prediction of twitter users with deep learning methodsJournal of Intelligent & Fuzzy Systems10.3233/JIFS-23051845:2(2723-2734)Online publication date: 1-Aug-2023
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