The Language of Legal and Illegal Activity on the Darknet

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

The Language of Legal and Illegal Activity on the Darknet. / Choshen, Leshem; Eldad, Dan; Hershcovich, Daniel; Sulem, Elior; Abend, Omri.

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 2019. p. 4271-4279.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Choshen, L, Eldad, D, Hershcovich, D, Sulem, E & Abend, O 2019, The Language of Legal and Illegal Activity on the Darknet. in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, pp. 4271-4279, 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, 01/07/2019.

APA

Choshen, L., Eldad, D., Hershcovich, D., Sulem, E., & Abend, O. (2019). The Language of Legal and Illegal Activity on the Darknet. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 4271-4279). Association for Computational Linguistics.

Vancouver

Choshen L, Eldad D, Hershcovich D, Sulem E, Abend O. The Language of Legal and Illegal Activity on the Darknet. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. 2019. p. 4271-4279

Author

Choshen, Leshem ; Eldad, Dan ; Hershcovich, Daniel ; Sulem, Elior ; Abend, Omri. / The Language of Legal and Illegal Activity on the Darknet. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 2019. pp. 4271-4279

Bibtex

@inproceedings{09f3830243c144f39af9eed52a6315a2,
title = "The Language of Legal and Illegal Activity on the Darknet",
abstract = "The non-indexed parts of the Internet (the Darknet) have become a haven for both legal and illegal anonymous activity. Given the magnitude of these networks, scalably monitoring their activity necessarily relies on automated tools, and notably on NLP tools. However, little is known about what characteristics texts communicated through the Darknet have, and how well do off-the-shelf NLP tools do on this domain. This paper tackles this gap and performs an in-depth investigation of the characteristics of legal and illegal text in the Darknet, comparing it to a clear net website with similar content as a control condition. Taking drugs-related websites as a test case, we find that texts for selling legal and illegal drugs have several linguistic characteristics that distinguish them from one another, as well as from the control condition, among them the distribution of POS tags, and the coverage of their named entities in Wikipedia.",
author = "Leshem Choshen and Dan Eldad and Daniel Hershcovich and Elior Sulem and Omri Abend",
year = "2019",
language = "English",
pages = "4271--4279",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics",
note = "57th Annual Meeting of the Association for Computational Linguistics ; Conference date: 01-07-2019 Through 01-07-2019",

}

RIS

TY - GEN

T1 - The Language of Legal and Illegal Activity on the Darknet

AU - Choshen, Leshem

AU - Eldad, Dan

AU - Hershcovich, Daniel

AU - Sulem, Elior

AU - Abend, Omri

PY - 2019

Y1 - 2019

N2 - The non-indexed parts of the Internet (the Darknet) have become a haven for both legal and illegal anonymous activity. Given the magnitude of these networks, scalably monitoring their activity necessarily relies on automated tools, and notably on NLP tools. However, little is known about what characteristics texts communicated through the Darknet have, and how well do off-the-shelf NLP tools do on this domain. This paper tackles this gap and performs an in-depth investigation of the characteristics of legal and illegal text in the Darknet, comparing it to a clear net website with similar content as a control condition. Taking drugs-related websites as a test case, we find that texts for selling legal and illegal drugs have several linguistic characteristics that distinguish them from one another, as well as from the control condition, among them the distribution of POS tags, and the coverage of their named entities in Wikipedia.

AB - The non-indexed parts of the Internet (the Darknet) have become a haven for both legal and illegal anonymous activity. Given the magnitude of these networks, scalably monitoring their activity necessarily relies on automated tools, and notably on NLP tools. However, little is known about what characteristics texts communicated through the Darknet have, and how well do off-the-shelf NLP tools do on this domain. This paper tackles this gap and performs an in-depth investigation of the characteristics of legal and illegal text in the Darknet, comparing it to a clear net website with similar content as a control condition. Taking drugs-related websites as a test case, we find that texts for selling legal and illegal drugs have several linguistic characteristics that distinguish them from one another, as well as from the control condition, among them the distribution of POS tags, and the coverage of their named entities in Wikipedia.

M3 - Article in proceedings

SP - 4271

EP - 4279

BT - Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

PB - Association for Computational Linguistics

T2 - 57th Annual Meeting of the Association for Computational Linguistics

Y2 - 1 July 2019 through 1 July 2019

ER -

ID: 239016644