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The where in the tweet

Published: 24 October 2011 Publication History

Abstract

Twitter is a widely-used social networking service which enables its users to post text-based messages, so-called tweets. POI tags on tweets can show more human-readable high-level information about a place rather than just a pair of coordinates. In this paper, we attempt to predict the POI tag of a tweet based on its textual content and time of posting. Potential applications include accurate positioning when GPS devices fail and disambiguating places located near each other. We consider this task as a ranking problem, i.e., we try to rank a set of candidate POIs according to a tweet by using language and time models. To tackle the sparsity of tweets tagged with POIs, we use web pages retrieved by search engines as an additional source of evidence. From our experiments, we find that users indeed leak some information about their accurate locations in their tweets.

References

[1]
Z. Cheng, J. Caverlee, and K. Lee. You are where you tweet: a content-based approach to geo-locating twitter users. CIKM '10.
[2]
F. de Jong, T. Westerveld, and A. de Vries. Multimedia search without visual analysis: The value of linguistic and contextual information. Circuits and Systems for Video Technology, IEEE Transactions on, 17(3).
[3]
B. Hecht, L. Hong, B. Suh, and E. H. Chi. Tweets from justin bieber's heart: the dynamics of the location field in user profiles. CHI '11.
[4]
A. Java, X. Song, T. Finin, and B. Tseng. Why we twitter: understanding microblogging usage and communities. WebKDD/SNA-KDD '07.
[5]
H. Kwak, C. Lee, H. Park, and S. Moon. What is Twitter, a social network or a news media? WWW '10.
[6]
A. Leuski and V. Lavrenko. Tracking dragon-hunters with language models. CIKM '06.
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M. Sahami and T. D. Heilman. A web-based kernel function for measuring the similarity of short text snippets. WWW '06.

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  • (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
  • (2022)MonkeyPox2022Tweets: A Large-Scale Twitter Dataset on the 2022 Monkeypox Outbreak, Findings from Analysis of Tweets, and Open Research QuestionsInfectious Disease Reports10.3390/idr1406008714:6(855-883)Online publication date: 14-Nov-2022
  • (2022)Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research QuestionsAnalytics10.3390/analytics10200071:2(72-97)Online publication date: 23-Sep-2022
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cover image ACM Conferences
CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
October 2011
2712 pages
ISBN:9781450307178
DOI:10.1145/2063576
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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Publication History

Published: 24 October 2011

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Author Tags

  1. geotag
  2. location-based estimation
  3. text mining
  4. twitter

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

View all
  • (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
  • (2022)MonkeyPox2022Tweets: A Large-Scale Twitter Dataset on the 2022 Monkeypox Outbreak, Findings from Analysis of Tweets, and Open Research QuestionsInfectious Disease Reports10.3390/idr1406008714:6(855-883)Online publication date: 14-Nov-2022
  • (2022)Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research QuestionsAnalytics10.3390/analytics10200071:2(72-97)Online publication date: 23-Sep-2022
  • (2022)A Location Recall Strategy for Improving Efficiency of User-Generated Short Text GeolocalizationIEEE Transactions on Computational Social Systems10.1109/TCSS.2021.31163419:5(1419-1431)Online publication date: Oct-2022
  • (2022)Sentiment-Based Spatiotemporal Prediction Framework for Pandemic Outbreaks Awareness Using Social Networks Data ClassificationIEEE Access10.1109/ACCESS.2022.319241710(76434-76469)Online publication date: 2022
  • (2022)Multi-feature, multi-modal, and multi-source social event detectionInformation Fusion10.1016/j.inffus.2021.10.01379:C(279-308)Online publication date: 1-Mar-2022
  • (2022)Twitter-aided decision making: a review of recent developmentsApplied Intelligence10.1007/s10489-022-03241-952:12(13839-13854)Online publication date: 1-Sep-2022
  • (2022)A Fine‐Grained Geolocalization Method for User Generated Short TextIEEJ Transactions on Electrical and Electronic Engineering10.1002/tee.2365917:10(1485-1494)Online publication date: 24-Jun-2022
  • (2021)Geolocation of Tweets in Spanish with Transformer Encoders2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT)10.1109/CONISOFT52520.2021.00038(227-231)Online publication date: Oct-2021
  • (2020)A Unified Translation of Linear Temporal Logic to ω-AutomataJournal of the ACM10.1145/341799567:6(1-61)Online publication date: 17-Oct-2020
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