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 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 drug-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.
| Original language | English |
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| Title of host publication | ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 4271-4279 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781950737482 |
| State | Published - 2020 |
| Event | 57th Annual Meeting of the Association for Computational Linguistics, ACL 2019 - Florence, Italy Duration: 28 Jul 2019 → 2 Aug 2019 |
Publication series
| Name | ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference |
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Conference
| Conference | 57th Annual Meeting of the Association for Computational Linguistics, ACL 2019 |
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| Country/Territory | Italy |
| City | Florence |
| Period | 28/07/19 → 2/08/19 |
Bibliographical note
Publisher Copyright:© 2019 Association for Computational Linguistics