Charting the Landscape of Online Cryptocurrency Manipulation
Cryptocurrencies represent one of the most attractive markets for financial speculation. As a consequence, they have attracted unprecedented attention on social media. Besides genuine discussions and legitimate investment initiatives, several deceptive activities have flourished. In this work, we ch...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9120022/ |
| _version_ | 1818732854510616576 |
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| author | Leonardo Nizzoli Serena Tardelli Marco Avvenuti Stefano Cresci Maurizio Tesconi Emilio Ferrara |
| author_facet | Leonardo Nizzoli Serena Tardelli Marco Avvenuti Stefano Cresci Maurizio Tesconi Emilio Ferrara |
| author_sort | Leonardo Nizzoli |
| collection | DOAJ |
| description | Cryptocurrencies represent one of the most attractive markets for financial speculation. As a consequence, they have attracted unprecedented attention on social media. Besides genuine discussions and legitimate investment initiatives, several deceptive activities have flourished. In this work, we chart the online cryptocurrency landscape across multiple platforms. To reach our goal, we collected a large dataset, composed of more than 50M messages published by almost 7M users on Twitter, Telegram and Discord, over three months. We performed bot detection on Twitter accounts sharing invite links to Telegram and Discord channels, and we discovered that more than 56% of them were bots or suspended accounts. Then, we applied topic modeling techniques to Telegram and Discord messages, unveiling two different deception schemes - “pump-and-dump” and “Ponzi” - and identifying the channels involved in these frauds. Whereas on Discord we found a negligible level of deception, on Telegram we retrieved 296 channels involved in pump-and-dump and 432 involved in Ponzi schemes, accounting for a striking 20% of the total. Moreover, we observed that 93% of the invite links shared by Twitter bots point to Telegram pump-and-dump channels, shedding light on a little-known social bot activity. Charting the landscape of online cryptocurrency manipulation can inform actionable policies to fight such abuse. |
| first_indexed | 2024-12-17T23:40:11Z |
| format | Article |
| id | doaj.art-481be63458404c54a616ec6b7c21beb5 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T23:40:11Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-481be63458404c54a616ec6b7c21beb52022-12-21T21:28:27ZengIEEEIEEE Access2169-35362020-01-01811323011324510.1109/ACCESS.2020.30033709120022Charting the Landscape of Online Cryptocurrency ManipulationLeonardo Nizzoli0https://orcid.org/0000-0002-9168-8992Serena Tardelli1https://orcid.org/0000-0002-7235-7055Marco Avvenuti2Stefano Cresci3Maurizio Tesconi4Emilio Ferrara5Institute of Informatics and Telematics, National Research Council (IIT-CNR), Pisa, ItalyInstitute of Informatics and Telematics, National Research Council (IIT-CNR), Pisa, ItalyDepartment of Information Engineering, University of Pisa, Pisa, ItalyInstitute of Informatics and Telematics, National Research Council (IIT-CNR), Pisa, ItalyInstitute of Informatics and Telematics, National Research Council (IIT-CNR), Pisa, ItalyInformation Sciences Institute, University of Southern California, Marina Del Rey, CA, USACryptocurrencies represent one of the most attractive markets for financial speculation. As a consequence, they have attracted unprecedented attention on social media. Besides genuine discussions and legitimate investment initiatives, several deceptive activities have flourished. In this work, we chart the online cryptocurrency landscape across multiple platforms. To reach our goal, we collected a large dataset, composed of more than 50M messages published by almost 7M users on Twitter, Telegram and Discord, over three months. We performed bot detection on Twitter accounts sharing invite links to Telegram and Discord channels, and we discovered that more than 56% of them were bots or suspended accounts. Then, we applied topic modeling techniques to Telegram and Discord messages, unveiling two different deception schemes - “pump-and-dump” and “Ponzi” - and identifying the channels involved in these frauds. Whereas on Discord we found a negligible level of deception, on Telegram we retrieved 296 channels involved in pump-and-dump and 432 involved in Ponzi schemes, accounting for a striking 20% of the total. Moreover, we observed that 93% of the invite links shared by Twitter bots point to Telegram pump-and-dump channels, shedding light on a little-known social bot activity. Charting the landscape of online cryptocurrency manipulation can inform actionable policies to fight such abuse.https://ieeexplore.ieee.org/document/9120022/Cryptocurrency manipulationsocial botsTwitterTelegramDiscord |
| spellingShingle | Leonardo Nizzoli Serena Tardelli Marco Avvenuti Stefano Cresci Maurizio Tesconi Emilio Ferrara Charting the Landscape of Online Cryptocurrency Manipulation IEEE Access Cryptocurrency manipulation social bots Telegram Discord |
| title | Charting the Landscape of Online Cryptocurrency Manipulation |
| title_full | Charting the Landscape of Online Cryptocurrency Manipulation |
| title_fullStr | Charting the Landscape of Online Cryptocurrency Manipulation |
| title_full_unstemmed | Charting the Landscape of Online Cryptocurrency Manipulation |
| title_short | Charting the Landscape of Online Cryptocurrency Manipulation |
| title_sort | charting the landscape of online cryptocurrency manipulation |
| topic | Cryptocurrency manipulation social bots Telegram Discord |
| url | https://ieeexplore.ieee.org/document/9120022/ |
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