research-article

Tag-geotag correlation in social networks

Authors:

Dennis McLeodAuthors Info & Claims

SSM '08: Proceedings of the 2008 ACM workshop on Search in social media

Pages 59 - 66

https://doi.org/10.1145/1458583.1458595

Published: 30 October 2008 Publication History

Abstract

This paper presents an analysis of the correlation of annotated information unit (textual) tags and geographical identification metadata geotags. Despite the increased usage of geotagging in collaborative tagging systems, most current research focuses on textual tagging alone in solving the tag search problem. This may result in difficulties to search for precise and relevant information within the given tag space. For example, inconsistencies like polysemy, synonyms, and word inflections with plural forms complicate the tag search problem. Therefore, more work needs to be done to include geotag information with existing tagging information for analysis. In this paper, to make geotagging possible to be used in analysis with tagging, we prove that there is a strong correlation between tagging and geotagging information. Our approach uses tag similarity and geographical distribution similarity to determine inter-relationships among tags and geotags. From our initial experiments, we show that the power law is established between tag similarity and geographical distribution similarity: this means that tag similarity and geographical distribution similarity has a strong correlation and the correlation can be used to find more relevant tags in the tag space. The power law confirms that there is an increased relationship between tagging and geotagging and the increased relationship is scalable in size of tags and geotags. Also, using both geotagging and tagging information instead of only tagging, we show that the uncertainty between derived and actual similarities among tags is reduced.

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Cited By

Zamiri MBahraini TYazdi H(2021)MVDF-RSC: Multi-view data fusion via robust spectral clustering for geo-tagged image taggingExpert Systems with Applications10.1016/j.eswa.2021.114657173(114657)Online publication date: Jul-2021
https://doi.org/10.1016/j.eswa.2021.114657
Han SRen FDu QGui D(2020)Extracting Representative Images of Tourist Attractions from Flickr by Combining an Improved Cluster Method and Multiple Deep Learning ModelsISPRS International Journal of Geo-Information10.3390/ijgi90200819:2(81)Online publication date: 31-Jan-2020
https://doi.org/10.3390/ijgi9020081
Zamiri MYazdi H(2020)Image Annotation based on Multi-view Robust Spectral ClusteringJournal of Visual Communication and Image Representation10.1016/j.jvcir.2020.103003(103003)Online publication date: Dec-2020
https://doi.org/10.1016/j.jvcir.2020.103003
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Index Terms

Tag-geotag correlation in social networks
1. Information systems
  1. Information retrieval
    1. Document representation

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Published In

cover image ACM Conferences

SSM '08: Proceedings of the 2008 ACM workshop on Search in social media

October 2008

106 pages

ISBN:9781605582580

DOI:10.1145/1458583

Program Chairs:
Ian Soboroff
National Institute of Standards and Technology
,
Eugene Agichtein
Emory University
,
Ravi Kumar
Yahoo! Research

Copyright © 2008 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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Published: 30 October 2008

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October 30, 2008

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Cited By

Zamiri MBahraini TYazdi H(2021)MVDF-RSC: Multi-view data fusion via robust spectral clustering for geo-tagged image taggingExpert Systems with Applications10.1016/j.eswa.2021.114657173(114657)Online publication date: Jul-2021
https://doi.org/10.1016/j.eswa.2021.114657
Han SRen FDu QGui D(2020)Extracting Representative Images of Tourist Attractions from Flickr by Combining an Improved Cluster Method and Multiple Deep Learning ModelsISPRS International Journal of Geo-Information10.3390/ijgi90200819:2(81)Online publication date: 31-Jan-2020
https://doi.org/10.3390/ijgi9020081
Zamiri MYazdi H(2020)Image Annotation based on Multi-view Robust Spectral ClusteringJournal of Visual Communication and Image Representation10.1016/j.jvcir.2020.103003(103003)Online publication date: Dec-2020
https://doi.org/10.1016/j.jvcir.2020.103003
Mackey PLewis R(2016)Parallel k-Means++ for Multiple Shared-Memory Architectures2016 45th International Conference on Parallel Processing (ICPP)10.1109/ICPP.2016.18(93-102)Online publication date: Aug-2016
https://doi.org/10.1109/ICPP.2016.18
Spyrou EMylonas P(2016)Analyzing Flickr metadata to extract location-based information and semantically organize its photo contentNeurocomputing10.1016/j.neucom.2014.12.104172(114-133)Online publication date: Jan-2016
https://doi.org/10.1016/j.neucom.2014.12.104
Feick RRobertson C(2015)A multi-scale approach to exploring urban places in geotagged photographsComputers, Environment and Urban Systems10.1016/j.compenvurbsys.2013.11.00653(96-109)Online publication date: Sep-2015
https://doi.org/10.1016/j.compenvurbsys.2013.11.006
Spyrou EMylonas P(2012)From Tags to Trends: A First Glance at Social Media Content DynamicsArtificial Intelligence Applications and Innovations10.1007/978-3-642-33412-2_44(431-441)Online publication date: 2012
https://doi.org/10.1007/978-3-642-33412-2_44
Sengstock CGertz M(2011)Exploration and comparison of geographic information sources using distance statisticsProceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/2093973.2094017(329-338)Online publication date: 1-Nov-2011
https://dl.acm.org/doi/10.1145/2093973.2094017
Spyrou EMylonas P(2011)Placing User-Generated Photo Metadata on a MapProceedings of the 2011 Sixth International Workshop on Semantic Media Adaptation and Personalization10.1109/SMAP.2011.16(79-84)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1109/SMAP.2011.16
Chandra SKhan LMuhaya F(2011)Estimating Twitter User Location Using Social Interactions--A Content Based Approach2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing10.1109/PASSAT/SocialCom.2011.120(838-843)Online publication date: Oct-2011
https://doi.org/10.1109/PASSAT/SocialCom.2011.120
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