Account Deletion Prediction on RuNet: A Case Study of Suspicious Twitter Accounts Active During the Russian-Ukrainian Crisis

Conference · Fri Jun 17 00:00:00 EDT 2016

DOI:https://doi.org/10.18653/v1/W16-0801· OSTI ID:1431411

Volkova, Svitlana; Bell, Eric B.

Social networks are dynamically changing over time e.g., some accounts are being created and some are being deleted or become private. This ephemerality at both an account level and content level results from a combination of privacy concerns, spam, and deceptive behaviors. In this study we analyze a large dataset of 180,340 accounts active during the Russian-Ukrainian crisis to discover a series of predictive features for the removal or shutdown of a suspicious account. We find that unlike previously reported profile and net- work features, lexical features form the basis for highly accurate prediction of the deletion of an account.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1431411
• Report Number(s): PNNL-SA-116813; 453040300
• Resource Relation: Conference: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2016), June 12-17, 2016, San Diego, California, 1-6
• Country of Publication: United States
• Language: English

Related Subjects

social media
deception
account deletion prediction
machine learning
natural language processing