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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Cited By

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
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
https://doi.org/10.1007/s00354-024-00276-z
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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

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
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
https://doi.org/10.1007/s00354-024-00276-z
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
https://doi.org/10.1007/978-3-031-58013-0_1
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
https://doi.org/10.3233/JIFS-230518
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Zhou FQi XZhang KTrajcevski GZhong T(2023)MetaGeo: A General Framework for Social User Geolocation Identification With Few-Shot LearningIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.315420434:11(8950-8964)Online publication date: Nov-2023
https://doi.org/10.1109/TNNLS.2022.3154204
Liu YLuo XTao ZZhang MDu S(2023)UGCC: Social Media User Geolocation via Cyclic CouplingIEEE Transactions on Big Data10.1109/TBDATA.2023.32429619:4(1128-1141)Online publication date: 1-Aug-2023
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Mandal DZou LAbedin JZhou BYang MLin BCai H(2023)Algorithmic uncertainties in geolocating social media data for disaster managementCartography and Geographic Information Science10.1080/15230406.2023.2286385(1-18)Online publication date: 21-Dec-2023
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