research-article

Inferring Friendship from Check-in Data of Location-Based Social Networks

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Yang ZhangAuthors Info & Claims

ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015

Pages 1284 - 1291

https://doi.org/10.1145/2808797.2808884

Published: 25 August 2015 Publication History

Abstract

With the ubiquity of GPS-enabled devices and location-based social network services, research on human mobility becomes quantitatively achievable. Understanding it could lead to appealing applications such as city planning and epidemiology. In this paper, we focus on predicting whether two individuals are friends based on their mobility information. Intuitively, friends tend to visit similar places, thus the number of their co-occurrences should be a strong indicator of their friendship. Besides, the visiting time interval between two users also has an effect on friendship prediction. By exploiting machine learning techniques, we construct two friendship prediction models based on mobility information. The first model focuses on predicting friendship of two individuals with only one of their co-occurred places' information. The second model proposes a solution for predicting friendship of two individuals based on all their co-occurred places. Experimental results show that both of our models outperform the state-of-the-art solutions.

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Y. Zhang and J. Pang, "Distance and friendship: A distance-based model for link prediction in social networks," in Proc. 17th Asia-Pacific Web Conference, ser. LNCS. Springer, 2015, accepted.

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Cited By

Züfle APfoser DWenk CCrooks AKavak HAnderson TKim JHolt NDiantonio A(2024)In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)ACM Transactions on Spatial Algorithms and Systems10.1145/367255710:2(1-27)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3672557
Chang STao YZhu HLi B(2023)FriendSeeker: Inferring Hidden Friendship in Mobile Social Networks with Sparse Check-in Data2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS57875.2023.00028(440-450)Online publication date: Jul-2023
https://doi.org/10.1109/ICDCS57875.2023.00028
Li YChen YQi TTian FWu YWang Q(2023)SHGAE: Social Hypergraph AutoEncoder for Friendship InferenceArtificial Neural Networks and Machine Learning – ICANN 202310.1007/978-3-031-44223-0_44(550-562)Online publication date: 22-Sep-2023
https://doi.org/10.1007/978-3-031-44223-0_44
Show More Cited By

Inferring Friendship from Check-in Data of Location-Based Social Networks
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
2. Information systems
  1. Information systems applications

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cover image ACM Conferences

ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015

August 2015

835 pages

ISBN:9781450338547

DOI:10.1145/2808797

Copyright © 2015 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: 25 August 2015

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ASONAM '15: Advances in Social Networks Analysis and Mining 2015

August 25 - 28, 2015

Paris, France

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Overall Acceptance Rate 116 of 549 submissions, 21%

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Cited By

Züfle APfoser DWenk CCrooks AKavak HAnderson TKim JHolt NDiantonio A(2024)In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)ACM Transactions on Spatial Algorithms and Systems10.1145/367255710:2(1-27)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3672557
Chang STao YZhu HLi B(2023)FriendSeeker: Inferring Hidden Friendship in Mobile Social Networks with Sparse Check-in Data2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS57875.2023.00028(440-450)Online publication date: Jul-2023
https://doi.org/10.1109/ICDCS57875.2023.00028
Li YChen YQi TTian FWu YWang Q(2023)SHGAE: Social Hypergraph AutoEncoder for Friendship InferenceArtificial Neural Networks and Machine Learning – ICANN 202310.1007/978-3-031-44223-0_44(550-562)Online publication date: 22-Sep-2023
https://doi.org/10.1007/978-3-031-44223-0_44
Wei XLiu YSun JJiang YTang QYuan K(2022)Dual Subgraph-Based Graph Neural Network for Friendship Prediction in Location-Based Social NetworksACM Transactions on Knowledge Discovery from Data10.1145/355498117:3(1-28)Online publication date: 16-Aug-2022
https://dl.acm.org/doi/10.1145/3554981
Ren LHu RLi DWu JZang YHu W(2022)Cross-Regional Friendship Inference via Category-Aware Multi-Bipartite Graph Embedding2022 IEEE 47th Conference on Local Computer Networks (LCN)10.1109/LCN53696.2022.9843580(73-80)Online publication date: 26-Sep-2022
https://doi.org/10.1109/LCN53696.2022.9843580
Lu XLi JWu CWu JDaneshmand M(2022)Measuring Similarity Between Any Pair of Passengers Using Smart Card Usage DataIEEE Internet of Things Journal10.1109/JIOT.2021.30896249:2(1458-1468)Online publication date: 15-Jan-2022
https://doi.org/10.1109/JIOT.2021.3089624
Ren LHu RLi DWang ZWu JLi XHu W(2022)Who is your friend: inferring cross-regional friendship from mobility profilesMultimedia Tools and Applications10.1007/s11042-022-13672-882:8(12719-12737)Online publication date: 19-Sep-2022
https://doi.org/10.1007/s11042-022-13672-8
Li YSang YChen WZhao L(2022)Linking Check-in Data to Users on Location-aware Social NetworksPRICAI 2022: Trends in Artificial Intelligence10.1007/978-3-031-20862-1_36(489-503)Online publication date: 4-Nov-2022
https://doi.org/10.1007/978-3-031-20862-1_36
John ECauthen KBrown NNozick L(2021)Detecting communities and attributing purpose to human mobility dataProceedings of the Winter Simulation Conference10.5555/3522802.3522844(1-12)Online publication date: 13-Dec-2021
https://dl.acm.org/doi/10.5555/3522802.3522844
John ECauthen KBrown NNozick L(2021)Detecting Communities and Attributing Purpose to Human Mobility Data2021 Winter Simulation Conference (WSC)10.1109/WSC52266.2021.9715396(1-12)Online publication date: 12-Dec-2021
https://doi.org/10.1109/WSC52266.2021.9715396
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