research-article

Object matching in tweets with spatial models

Authors:

Bo PangAuthors Info & Claims

WSDM '12: Proceedings of the fifth ACM international conference on Web search and data mining

Pages 43 - 52

https://doi.org/10.1145/2124295.2124303

Published: 08 February 2012 Publication History

Abstract

Despite their 140-character limitation, tweets embody a lot of valuable information, especially temporal and spatial. In this paper we study the geographic aspects of tweets, for a given object domain. We propose a user-level model for spatial encoding in tweets that goes beyond the explicit geo-coding or place name mentions; this model can be used to match objects to tweets. We illustrate our model and methodology using restaurants as the objects, and show a significant improvement in performance over using standard language models. En route, we obtain a method to geolocate users who tweet about geolocated objects; this may be of independent interest.

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Cited By

Smith DMac VHertzberg V(2021)Using Twitter for Nursing Research: A Tweet Analysis on Heat Illness and HealthJournal of Nursing Scholarship10.1111/jnu.1265453:3(343-350)Online publication date: 23-Mar-2021
https://doi.org/10.1111/jnu.12654
Mousset PPitarch YTamine L(2020)End-to-End Neural Matching for Semantic Location Prediction of TweetsACM Transactions on Information Systems10.1145/341514939:1(1-35)Online publication date: 5-Sep-2020
https://dl.acm.org/doi/10.1145/3415149
Giglio SBertacchini FBilotta EPantano P(2019)Machine learning and points of interest: typical tourist Italian citiesCurrent Issues in Tourism10.1080/13683500.2019.163782723:13(1646-1658)Online publication date: 12-Jul-2019
https://doi.org/10.1080/13683500.2019.1637827
Show More Cited By

Index Terms

Object matching in tweets with spatial models
1. Information systems
  1. Information retrieval
  2. Information storage systems

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Published In

cover image ACM Conferences

WSDM '12: Proceedings of the fifth ACM international conference on Web search and data mining

February 2012

792 pages

ISBN:9781450307475

DOI:10.1145/2124295

General Chairs:
Eytan Adar
University of Michigan, USA
,
Jaime Teevan
Microsoft Research, USA
,
Program Chairs:
Eugene Agichtein
Emory University, USA
,
Yoelle Maarek
Yahoo! Research, Israel

Copyright © 2012 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: 08 February 2012

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WSDM'12

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WSDM'12: Fifth ACM International Conference on Web Search and Data Mining

February 8 - 12, 2012

Washington, Seattle, USA

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Cited By

Smith DMac VHertzberg V(2021)Using Twitter for Nursing Research: A Tweet Analysis on Heat Illness and HealthJournal of Nursing Scholarship10.1111/jnu.1265453:3(343-350)Online publication date: 23-Mar-2021
https://doi.org/10.1111/jnu.12654
Mousset PPitarch YTamine L(2020)End-to-End Neural Matching for Semantic Location Prediction of TweetsACM Transactions on Information Systems10.1145/341514939:1(1-35)Online publication date: 5-Sep-2020
https://dl.acm.org/doi/10.1145/3415149
Giglio SBertacchini FBilotta EPantano P(2019)Machine learning and points of interest: typical tourist Italian citiesCurrent Issues in Tourism10.1080/13683500.2019.163782723:13(1646-1658)Online publication date: 12-Jul-2019
https://doi.org/10.1080/13683500.2019.1637827
Wei HSankaranarayanan JSamet H(2018)Enhancing Local Live Tweet Stream to Detect NewsProceedings of the 2nd ACM SIGSPATIAL Workshop on Analytics for Local Events and News10.1145/3282866.3282868(1-10)Online publication date: 6-Nov-2018
https://dl.acm.org/doi/10.1145/3282866.3282868
Zhang YHumbert MRahman TLi CPang JBackes MChampin PGandon FMédini LLalmas MIpeirotis P(2018)TagvisorProceedings of the 2018 World Wide Web Conference10.1145/3178876.3186095(287-296)Online publication date: 10-Apr-2018
https://dl.acm.org/doi/10.1145/3178876.3186095
Yu ZYi FLv QGuo B(2018)Identifying On-Site Users for Social Events: Mobility, Content, and Social RelationshipIEEE Transactions on Mobile Computing10.1109/TMC.2018.279498117:9(2055-2068)Online publication date: 1-Sep-2018
https://doi.org/10.1109/TMC.2018.2794981
Zheng XHan JSun A(2018)A Survey of Location Prediction on TwitterIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.280784030:9(1652-1671)Online publication date: 1-Sep-2018
https://doi.org/10.1109/TKDE.2018.2807840
Han JSun ACong GZhao WJi ZPhan M(2018)Linking Fine-Grained Locations in User CommentsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.275878030:1(59-72)Online publication date: 1-Jan-2018
https://doi.org/10.1109/TKDE.2017.2758780
Shen WHan JWang JYuan XYang Z(2018)SHINE+: A General Framework for Domain-Specific Entity Linking with Heterogeneous Information NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.273086230:2(353-366)Online publication date: 1-Feb-2018
https://doi.org/10.1109/TKDE.2017.2730862
Wei HSankaranarayanan JSamet H(2017)Finding and Tracking Local Twitter Users for News DetectionProceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/3139958.3141797(1-4)Online publication date: 7-Nov-2017
https://dl.acm.org/doi/10.1145/3139958.3141797
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