The Language of Legal and Illegal Activity on the Darknet
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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
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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