VASSL: A Visual Analytics Toolkit for Social Spambot Labeling.
IEEE Trans Vis Comput Graph
; 26(1): 874-883, 2020 01.
Article
en En
| MEDLINE
| ID: mdl-31425086
Social media platforms are filled with social spambots. Detecting these malicious accounts is essential, yet challenging, as they continually evolve to evade detection techniques. In this article, we present VASSL, a visual analytics system that assists in the process of detecting and labeling spambots. Our tool enhances the performance and scalability of manual labeling by providing multiple connected views and utilizing dimensionality reduction, sentiment analysis and topic modeling, enabling insights for the identification of spambots. The system allows users to select and analyze groups of accounts in an interactive manner, which enables the detection of spambots that may not be identified when examined individually. We present a user study to objectively evaluate the performance of VASSL users, as well as capturing subjective opinions about the usefulness and the ease of use of the tool.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
IEEE Trans Vis Comput Graph
Asunto de la revista:
INFORMATICA MEDICA
Año:
2020
Tipo del documento:
Article
Pais de publicación:
Estados Unidos