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Twitter User Location Inference Based on Representation Learning and Label Propagation

Authors:

Yaqiong QiaoAuthors Info & Claims

WWW '20: Proceedings of The Web Conference 2020

Pages 2648 - 2654

https://doi.org/10.1145/3366423.3380019

Published: 19 April 2020 Publication History

Abstract

Social network user location inference technology has been widely used in various geospatial applications like public health monitoring and local advertising recommendation. Due to insufficient consideration of relationships between users and location indicative words, most of existing inference methods estimate label propagation probabilities solely based on statistical features, resulting in large location inference error. In this paper, a Twitter user location inference method based on representation learning and label propagation is proposed. Firstly, the heterogeneous connection relation graph is constructed based on relationships between Twitter users and relationships between users and location indicative words, and relationships unrelated to geographic attributes are filtered. Then, vector representations of users are learnt from the connection relation graph. Finally, label propagation probabilities between adjacent users are calculated based on vector representations, and the locations of unknown users are predicted through iterative label propagation. Experiments on two representative Twitter datasets - GeoText and TwUs, show that the proposed method can accurately calculate label propagation probabilities based on vector representations and improve the accuracy of location inference. Compared with existing typical Twitter user location inference methods - GCN and MLP-TXT+NET, the median error distance of the proposed method is reduced by 18% and 16%, respectively.

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Liu TMa ZLiu YKang XZhang BMa J(2024)A Privacy-Preserving Computation Framework for Multisource Label Propagation ServicesIEEE Transactions on Services Computing10.1109/TSC.2024.3486196(1-14)Online publication date: 2024
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Twitter User Location Inference Based on Representation Learning and Label Propagation

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Published In

cover image ACM Conferences

WWW '20: Proceedings of The Web Conference 2020

April 2020

3143 pages

ISBN:9781450370233

DOI:10.1145/3366423

Editors:
Yennun Huang
Acadmica sinica, Taiwan
,
Irwin King
The Chinese University of Hong Kong, Hong Kong
,
Tie-Yan Liu
Microsoft Research Asia, China
,
Maarten van Steen
University of Twente, Netherlands

Copyright © 2020 ACM.

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Published: 19 April 2020

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WWW '20: The Web Conference 2020

April 20 - 24, 2020

Taipei, Taiwan

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Kageyama SInui T(2024)Effectiveness of the Geographical Specificity Index in Document Geolocation文書ジオロケーション課題における地理的特定性指標の有効性評価Journal of Natural Language Processing10.5715/jnlp.31.166531:4(1665-1690)Online publication date: 2024
https://doi.org/10.5715/jnlp.31.1665
Liu TMa ZLiu YKang XZhang BMa J(2024)A Privacy-Preserving Computation Framework for Multisource Label Propagation ServicesIEEE Transactions on Services Computing10.1109/TSC.2024.3486196(1-14)Online publication date: 2024
https://doi.org/10.1109/TSC.2024.3486196
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
Vargo CMinooie M(2024)Breaking Agenda Setting Boundaries: A Multi-Dimensional Approach to Understanding Salience of Gun Control in the Polarized Public SphereMass Communication and Society10.1080/15205436.2024.2333972(1-24)Online publication date: 16-Apr-2024
https://doi.org/10.1080/15205436.2024.2333972
Guo Yvanden Broucke S(2024)Enhancing geospatial prediction models with feature engineering from road networks: a graph-driven approachInternational Journal of Geographical Information Science10.1080/13658816.2024.234874038:8(1611-1632)Online publication date: 6-May-2024
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Zhang MLuo XHuang N(2024)Social Media User Geolocation Based on Large Language ModelsData Security and Privacy Protection10.1007/978-981-97-8540-7_19(304-312)Online publication date: 18-Oct-2024
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Qiao YLuo XMa JZhang MLi C(2023)Twitter user geolocation based on heterogeneous relationship modeling and representation learningInformation Sciences10.1016/j.ins.2023.119427647(119427)Online publication date: Nov-2023
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