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VisPaD: Visualization and Pattern Discovery for Fighting Human Trafficking

Published: 16 August 2022 Publication History

Abstract

Human trafficking analysts investigate groups of related online escort advertisements (called micro-clusters) to detect suspicious activities and identify various modus operandi. This task is complex as it requires finding patterns and linked meta-data across micro-clusters such as the geographical spread of ads, cluster sizes, etc. Additionally, drawing insights from the data is challenging without visualizing these micro-clusters. To address this, in close-collaboration with domain experts, we built VisPaD, a novel interactive way for characterizing and visualizing micro-clusters and their associated meta-data, all in one place. VisPaD helps discover underlying patterns in the data by projecting micro-clusters in a lower dimensional space. It also allows the user to select micro-clusters involved in suspicious patterns and interactively examine them leading to faster detection and identification of trends in the data. A demo of VisPaD is also released1.

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Aayushi Kulshrestha. 2021. Detection of Organized Activity in Online Escort Advertisements.
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Meng-Chieh Lee, Catalina Vajiac, Aayushi Kulshrestha, Sacha Levy, Namyong Park, Cara Jones, Reihaneh Rabbany, and Christos Faloutsos. 2021. InfoShield: Generalizable Information-Theoretic Human-Trafficking Detection. In IEEE ICDE. IEEE.
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Lin Li, Olga Simek, Angela Lai, Matthew P. Daggett, Charlie K. Dagli, and Cara Jones. 2018. Detection and Characterization of Human Trafficking Networks Using Unsupervised Scalable Text Template Matching. In IEEE BigData. IEEE, 3111–3120.
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United Nations News. 2021. Traffickers abusing online technology, UN crime prevention agency warns. https://news.un.org/en/story/2021/10/1104392.
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  1. VisPaD: Visualization and Pattern Discovery for Fighting Human Trafficking

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    cover image ACM Conferences
    WWW '22: Companion Proceedings of the Web Conference 2022
    April 2022
    1338 pages
    ISBN:9781450391306
    DOI:10.1145/3487553
    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: 16 August 2022

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    Author Tags

    1. cluster visualization
    2. pattern discovery
    3. social good

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    • CIFAR AI Chairs program

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    WWW '22
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    WWW '22: The ACM Web Conference 2022
    April 25 - 29, 2022
    Virtual Event, Lyon, France

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