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I seek you: searching and matching individuals in social networks

Published: 02 November 2009 Publication History
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  • Abstract

    The first task any individual faces after joining an online social network (OSN) is locating friends that are present on that particular site. Most OSNs offer some variation of a tool that imports email contact lists to facilitate the task of finding one's friends. However, given that OSNs attempt to reconnect individuals with past acquaintances, one might not have access to the email address for a long lost friend. Furthermore, people tend to utilize a number of aliases online, meaning that an email address cannot always be used to reliably find a friend. Thus, new members must still manually search for friends based on a number of biographical attributes, such as gender, age, hometown, etc. It is not clear, however, what attributes are useful for conducting the search. Even after the search has been performed, the person performing the search might be left with a number of candidate profiles. In this paper, we develop a system for searching and matching individuals in OSNs. We evaluate the efficacy of our person matching techniques by measuring the overlap between social networks, and comparing our results to those published by compete.com. We then look at several interesting properties of overlapping profiles in both networks.

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    cover image ACM Conferences
    WIDM '09: Proceedings of the eleventh international workshop on Web information and data management
    November 2009
    104 pages
    ISBN:9781605588087
    DOI:10.1145/1651587
    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: 02 November 2009

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    Author Tags

    1. analysis
    2. crawling
    3. social networks

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    • (2024)User Identification Across Multiple Social Networks Based on Naive Bayes ModelIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.320270935:3(4274-4285)Online publication date: Mar-2024
    • (2024)A Trajectory-oriented Locality-sensitive Hashing Method for User IdentificationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.3324427(1-14)Online publication date: 2024
    • (2024)An Account Matching Method Based on Hyper GraphInformation Security and Privacy10.1007/978-981-97-5028-3_22(433-452)Online publication date: 16-Jul-2024
    • (2023)Semi-Supervised Variational User Identity Linkage via Noise-Aware Self-LearningIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.325024535:10(10166-10180)Online publication date: 1-Oct-2023
    • (2023)A Binary-Search-Based Locality-Sensitive Hashing Method for Cross-Site User IdentificationIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.315866410:2(480-491)Online publication date: Apr-2023
    • (2023)Optimizing user profile matching: a text-based approachInternational Journal of Computers and Applications10.1080/1206212X.2023.221824445:5(403-412)Online publication date: 30-May-2023
    • (2023)User identification for knowledge graph construction across multiple online social networksAlexandria Engineering Journal10.1016/j.aej.2023.04.03573(145-158)Online publication date: Jul-2023
    • (2023)SiMAIM: identifying sockpuppets and puppetmasters on a single forum-oriented social media siteThe Journal of Supercomputing10.1007/s11227-023-05376-z79:16(18667-18698)Online publication date: 17-May-2023
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    • (2022)SOIDP: Predicting Interlayer Links in Multiplex NetworksIEEE Transactions on Computational Social Systems10.1109/TCSS.2021.30684689:4(997-1007)Online publication date: Aug-2022
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